Me:
“Alexa, tell me what will happen in 2019.”
Amazon
AI: “Do you want to open ‘this day in history'?"
Me:
“Alexa, give me a prediction for 2019.”
Amazon
AI: “The crystal ball is clouded, I can’t tell.”
My
conversation with Amazon’s “smart speaker” or “intelligent voice assistant”
just about sums up the present state of “artificial intelligence” (AI) at home,
the office, and the factory: Try a few times and sooner or later you will
probably get the correct action the human intelligence behind it programmed it
to perform.
What
will be the state of AI in 2019?
Today In: Innovation
The
following list features 120 senior executives involved with AI, all peering
into their not-so-clouded crystal ball, and promising less hype and more
practical, precise, and narrow AI.
“Self-Driving
Finance is a practical implementation of AI that is already used in one form or
another by millions of bank customers around the globe and will only get better
in the coming years. Based on projects that are currently underway with banks
at different parts of the world, I see a big uptake in the number of
customers that will rely on AI to ‘drive’ their finances and take automated
actions to help them reach their financial goals. To deliver effective
Self-Driving Finance, financial institutions will require specialized forms of
AI for each of their customer segments such as retail, small business, and
wealth—moving away from more generic forms of AI towards domain-specific solutions
that embed subject matter knowledge and expertise”—David Sosna, Co-founder and
CEO, Personetics
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“2019
will be the year of specialized AI systems built by organizations based on their
own data. Given the realization that organizations sometimes have only
limited amounts of data, but also require specialized data, organizations will
come to realize that they need tools to easily create quality AI data
internally. This quality over quantity approach will require organizations to
take stock of the data they have and ask themselves key questions: is this data
representative of what I’m looking for, and does it match my goal? Will the
production data match this training data? Did I strike a balance between
repeatability of images and variation? Is my dataset diverse? Taking new
approaches to data strategy will be make-or-break for overcoming the challenges
of AI’s data problem, to develop AI that works in the real world”—Max Versace,
PhD, CEO and co-founder, Neurala
“AI
will enable greater process discovery. Process discovery is like a
sensor embedded in the application that learns all of the user journeys, using
AI to predict the optimal path for interacting with a system. Similar to using
a GPS such as Waze when you're driving to unlock optimal routes depending on
the time of day, AI will unlock how each employee can best use a system,
providing a range of possibilities based on what the individual needs to
do”—Rephael Sweary, Co-founder and President, WalkMe
"In
2019, we will start to see technology that will allow designers to talk to
computer programs powered by AI to redesign, optimize and lightweight parts
made by 3D printers in real time. The designer will simply articulate
the design goals and material parameters and the AI will do the rest—exploring
nearly infinite design permutations based on existing design concepts. More
power will be put into the hands of designers who will be better able to test
and experiment with alterations to create optimal designs much faster than
before”—Avi Reichental, Founder and CEO, XponentialWorks
“Because
of cloud and the pervasiveness of APIs, in 2019 we’ll begin to see AI
deliver meaningful value to the enterprise and get us closer to the Holy Grail
of AI, which is helping people at all levels of an organization do what
they do more effectively and efficiently, while uncovering new opportunities
and new ways to work”—Josh James, Founder and CEO, Domo
“While
B2B providers have been slow to adapt to the high standard of personalized
digital experiences set by Amazon and Google, the industry has at least
acknowledged the value of personalized home and landing pages. As customer
expectations increase, enterprises will need to keep pace by using
machine learning and AI to offer a personalized experience beyond the first
impression, which extends to other assets such as technical documentation,
community portals, and chatbots”—Gal Oron, CEO, Zoomin
“In
2018 we saw a great deal of hype around AI in healthcare but we also saw it
become a reality—in everything from predictive analytics for chronic disease
management, to workflow enhancement in radiology as well as administrative and
financial use cases that bring operational efficiency. In 2019 we are
going to see voice and video, coupled with AI, being used to help accelerate
the shift of the point of care from the hospital, to the patient, wherever they
are. The convergence of AI with 5G will also accelerate the development
of digital therapeutics that are more personalized, adaptive and take advantage
of AR and VR. Mental health and substance abuse treatment will be where we
see early adoption. Clinicians that embrace AI as an augmenter or assistant,
not as a threat of replacement or obsolescence, will be able to
differentiate themselves both to their patients and their peers”—Jennifer
Esposito, General Manager, Health & Life Sciences, Intel
“AI
plays an increasing critical role in several industries from translating text
and powering industrial drones to patient diagnosis. In 2019, we expect
AI, and more precisely image recognition, to be integrated into everyday life
tasks such as helping those with disabilities and automating cars. AI
will also become part of the everyday shopping experience as existing stores
will become automated, driving supply chain processes, delivering seamless
checkout and enhancing customer engagement”—Michael Gabay, CEO, Trigo
Vision
“AI
will accelerate the end of ownership.” Today, we don’t own movies or music
anymore—we subscribe to Netflix or Spotify. Tomorrow, we won’t own products anymore—we’ll
subscribe to them. AI platforms are in the midst of turning every manufactured
product on the planet into a connected ‘smart’ product. Today you can see that
trend happening in transportation and consumer electronics—cars, scooters,
washing machines, coffee makers, thermostats, etc. But soon you’ll start seeing
it happen everywhere—tables, chairs, floors, walls, clothes. As a result, we
won’t need to own anything. We’ll simply subscribe to services: housing
services, food services, transportation services, furniture services, clothing
services. We’ll be living in a true Subscription Economy”– Tien Tzuo, CEO & Founder, Zuora
“Automation
plays into the hands of a cyber attacker, allowing him to use simpler tools to
gain access and infiltrate networks. However, automation used in defense is not
creating anywhere near the same impact. Two core factors can be attributed to
this, namely a very limited talent pool and that the technology only works as
well as the reliability of the data. Until the false positive problem is
resolved, automation is not full-proof. Instead, automation should
primarily be leveraged pre-breach, serving as a proactive defense mechanism to
help organizations outmaneuver the attacker at the earliest stage and
minimize the potential damage”—Nadav Zafrir, CEO, Team8
“Robotics
and AI are increasingly used hand-in-hand to inspect and ensure the proper
functioning of critical infrastructure that our society is built on—power
lines, railroad tracks, flare stacks etc. Next year, the convergence of these
two technologies is poised to accelerate, with 2019 serving as a
breakout year for Distributed AI, in which intelligence will decentralize
and be embedded closer to the assets and devices carrying out the inspections.
Today’s cloud systems that remotely control Industrial IoT and AI - often at
significant distances from inspection sites - will begin transitioning to
distributed and autonomous systems closer to the source of inspections, making
inspection data collection more efficient and safer”—Ashish Jain, Managing
Director of Data Sciences, GE Ventures
“Artificial
Intelligence (AI) and Machine Learning have been hot topics for a while, but
that will begin to decline in 2019. With many enterprises once having built an 'AI
strategy,' today we’re already finding that more and more are moving away from
the hype and into solving real-world problems. We will see the focus
shift from AI to 'AI-driven' results as companies look for real
business impact from AI tools. The technology will be less important than the
business insights it delivers”—Sean Byrnes, CEO and co-founder, Outlier
“The
consumer's understanding around AI will shift dramatically. We will no
longer associate AI with futuristic robots and self-driving cars, but
rather productivity tools and predictions to help everyday menial tasks”—Josh
Poduska, Chief Data Scientist, Domino Data Lab
“2019
will be the year of the death of the data scientist. In 2019,
everybody is going to start learning Artificial Intelligence (AI) and the
domain of data science will no longer be a purist data scientist. There are
only about 5,000 folks who are data scientists and we can’t rely on them to
lead an industrial revolution. Everyone within an organization needs to have AI
skills, from product managers to business analysts. The death of the data
scientist is the pinnacle of this revolution”—Aman Naimat, CTO, Demandbase
“Some
of our AI emperors have no clothes. For years, hot AI startups raised, scaled,
and raced to build powerful algorithms in nearly every vertical—law, medicine,
fintech—the list goes on. These AI solutions were framed as replacements for
your most menial tasks. A new wave is on the horizon—AI startups that
generate proprietary data every time they're used. These startups, which
leverage what we call Coaching Networks, are powered by algorithms that forever
improve because they're fueled by the creative inputs and successes of millions
of workers. These focused networks will be very hard for companies that
leverage static data sets and commodity APIs to compete with”—Gordon Ritter,
General Partner, Emergence
“AI
is already outperforming humans in many domain-specific tasks; now comes
the age of real-world applications. In
2019, AI will fundamentally disrupt diabetes management, thereby
improving the lives of millions. Moreover, AI will help bring
to life the ample information gathered from wearables,
transforming it into actionable insights that will
help people lead healthier lives. In addition, there will be a
big leap in unsupervised machine learning in the near future. Finally, I
we will see companies using AI to train AI. Instead of data scientists trying
to experiment on which AI models work better for real world problems, companies
will let AI do the work for them. This will help AI outperform humans in many new
tasks”—Yaron Hadad, Chief Scientist and Co-Founder, Nutrino
“If
we want to create AI which is actually adopted by humans, it will have to be
less and less ‘artificial,’ and more and more ‘intelligent,’ meaning it will
have to take on human traits. For people to feel a connection to AI-powered
services and be willing to adopt them into every aspect of their lives, these
services will have to become more and more anthropomorphized. And just as the
human body is able to heal itself, we will also expect these systems to
self-diagnose problems in their code and self-heal, correcting software issues
on their own”—Zohar Fox, CEO and Co-Founder, Aurora
Labs
“We
believe AI as an all-purpose buzzword in healthcare will be slowly retired in
2019. As digitization of the industry matures, the idea of the
all-knowing machine replacing doctors is clearly being debunked. The
challenges of IBM Watson’s healthcare efforts,
for example, illustrate that powerful computational tools alone are
ineffective in the face of unstructured medical data and the complex realities
of patient care. For 2019 we are skeptical about broad, systems-based uses of
artificial intelligence promising unspecified insights”—Yonatan Adiri, Founder
and CEO, Healthy.io
“In
2019, not only will developing more robust and sophisticated AI algorithms take
center stage, but as these AI algorithms become more unique and effective, they
will also grow in value and owners will have to protect their substantial
investment. Companies are spending millions to develop AI, and they are often
at the heart of business growth, yet new security challenges have emerged
around protecting these AI models—securing their intellectual property
from being stolen while also ensuring that no one is tampering with the
model. In 2019, we will have to be deeply intelligent about protecting
our Artificial Intelligence”—Alon Kaufman, Co-founder and CEO, Duality
Technologies
“Until
now, the use of AI has been focused on making our lives more automated and our
industries smarter. In 2019, we are going to see a shift toward
utilizing AI for social good and making our lives more sustainable. AI
is going to be used to make our cities and industries more environmentally
friendly and our world a better place. From agritech and crop optimization to
utilities and alternative energy, the big data analytics and machine learning
behind AI will be leveraged to completely change the way consumers interact
with their surroundings”—Natan Barak, CEO and Founder, mPrest
"In
2019, the global lending sector will see an uptick in AI that can predict
financial eligibility and funding opportunities. With AI, lenders can
foresee which of today’s unviable applicants will become creditworthy in
the future, thus open funding opportunities to businesses previously locked
behind low-tech assessment processes. The dynamic and real-time nature of AI will
provide continuous and automatic access to and updates about new financing
opportunities that arise throughout a business’s lifespan, as it grows and
improves. This same AI application will eventually change the mortgage and
student loan industry as well”—Eden Amirav, CEO and Co-founder, Lending Express
“The
AI that supports prediction in self-driving cars will be ‘remodeled’ to access
and analyze predictionary data differently. The Autonomous Vehicle industry
will move away from object fusion and towards raw data fusion, which enables
AVs to better interpret movement, speed, angle, and trajectory, and provides
rich data to predict the direction and future movement of an object,
pedestrian, or vehicle”—Ronny Cohen, CEO and Co-founder, VAYAVISION
“Multi-trillion-dollar
markets such as commercial real estate are comprised of an intricate web of
interactions that affect every decision, and AI technology is now mature enough
to tackle these highly complex transactions. As industry leaders are opening up
to the potential of integrating advanced technology into core operations, AI
is making its impact felt across new industries that were previously off limits.
We see asset managers looking to develop new investment vehicles defined by AI
that will enable enhanced performance in uncertain economic conditions, adding
value throughout the entire investment lifecycle”—Guy Zipori, CEO, Skyline
AI
“Even
though level 4 and 5 autonomous vehicles (AVs) still aren’t commercially
available, 2019 will be the year that they take a giant leap forward. The
data that AI relies on will become more readily accessible thanks to
data-sharing alliances that must become a reality in order for automotive AI to
improve to a level suitable for all road conditions. Simultaneously, the types
of data collected for AI will be broadened to include non-visual data. Better
data means better AI and safer AVs”—Boaz Mizrachi, Founder & CTO, Tactile
Mobility
"As
more businesses rely on AI to fuel their own products, services and data-driven
marketing innovations, bad actors across the digital ecosystem will utilize
similar capabilities to increase their efforts and execute massive fraud
schemes, resulting in hundreds of millions of dollars in losses for brands and
marketers. With that, companies that invest smartly in AI and machine
learning-based fraud protection tools will be able to clearly ‘see’ the entire
ecosystem and protect themselves from fraud and the polluted data that impacts
business decisions—leading to a significant competitive advantage"—Ran
Avrahamy, VP, Global Marketing, AppsFlyer
“AI
research and applications are proving increasingly important in healthcare,
improving patient outcomes through a more personalized, data-driven approach.
Just as big data is used to curate more satisfying user experiences, more
granular ‘small data’—information generated by each individual
and analyzed by AI tools, turning smartphones and consumer wearables
into powerful at-home diagnostic and treatment tools—will be used to drive
digital health users to action based on their real-world behavior,
capabilities and needs, and to boost population health by making disease
prediction and prevention scalable. In 2019, AI will be the
linchpin of digital health’s application to the prevention and treatment of
disease, specifically chronic illnesses, connecting the dots
between the small data that can optimize an individual’s personal care and the
big data that can uncover solutions with a global impact”—Dana Chanan, CEO and
Co-Founder, Sweetch
“2019
will be a pivotal year in the way cities understand their urban mobility
ecosystems in order to build much more efficient transportation systems
throughout urban areas. If today’s cities are primarily focused on
severe challenges such as traffic, pollution and lack of parking space, in 2019
they will have far better visibility into the root cause—inefficiency of
movement in urban areas. Understanding how people are moving in urban
areas, from where to where, when, with which means of transportation, and
understanding why—that’s the core that will allow cities to build more
efficient mobility, reducing our need to move around, encouraging people to
move together, and creating multimodality. In order to get there, cities will
need visibility into such data, and AI is precisely the tool that will enable
such visibility, fostering prediction capabilities and action points to
significantly improve the way we move”—Liad Itzhak, SVP Head, HERE
Mobility
“There
is no shortage of angst when it comes to the impact of AI on jobs, especially
within the agricultural industry. However, the future of precision agriculture
and the key to growing a better crop will rely on AI, imagery and sensors that
will be able to learn from collecting information cultivated from 1000-acre
farms. Agronomists and farmers are facing a major labor shortage and lack of
expertise. The demand for food is increasing, yet farming is not valued as an
attractive or profitable career, particularly in commodity crops. Due to the
size and diversity of farming operation demands, farmers need to pay close
attention to labor initiatives and employee management. Farms across
the world are moving to fill the labor gap—not replace jobs—with AI
technology”—Ofir Schlam, CEO and Cofounder, Taranis
“Brick-and-Mortar
retail businesses are turning their attention to AI to significantly improve
customer experience, profitability and remain competitive. In 2019, we
will see emergence of new data sources (surveillance cameras,
on-the-shelf-cameras, robots) and AI models for inventory management, better
customer retail experiences, targeted marketing, and adding new capabilities
such as self-checkout. The key challenge, however, is to develop and
scale AI operations to thousands of retail stores that differ in planograms,
camera models, and network infrastructure capabilities”—Atif Kureishy, Vice
President Global Emerging Practices, Teradata
"I
expect we'll see AI-based attribution tools hitting their stride in 2019. In
today’s digital environment, attribution continues to be a challenge—businesses
are still piecing together data points from different platforms and many are
still struggling to understand the full path to purchase—which marketing
channels are driving revenue? What kinds of content help retain customers and
at which stage of the customer journey? Where are customers falling out of the
funnel? AI can sequence the customer journey together and identify when
a customer comes to a company's site and leaves without converting. It's
the businesses that adopt AI-powered attribution tools that will have a leg up
on the competition"—Carl Schmidt, CTO and co-founder, Unbounce
“The
future of third-party data is critical for marketers to stay actionable and
competitive in a fast-moving technology landscape. The culmination of
high-profile corporate privacy scandals and new wide-sweeping data legislation
has forced consumers to get to grips with their digital footprints and has
caused them to be more critical over how they are targeted. Moving
forward, third party data will help marketers gather more insights surrounding
how consumers use emerging technologies such as voice, location-based search
and AI, so they can target them in a way that is compliant and drives ROI.
This data will remain key to informing the bulk of marketing strategy for years
to come"—Chase Buckle, Senior Trends Analyst, GlobalWebIndex
“The
hype around AI technologies that match human intelligence in some abstract form
is drowning out the fact that today, there is real value in AI tools that
collect, organize and make actionable the collective human experience. AI is
not HAL 9000 from Space Odyssey. In 2019, AI will be about making people
smarter, more effective, and more productive. It will also make people happier
in their jobs – especially IT professionals. For enterprise IT, 2019
will be the year that AI will enable teams to move beyond simple task
automation, to empower the robotization of entire processes. By tapping the
applied collective knowledge of thousands of users and millions of process
executions with AI, IT teams will be able to preemptively streamline
application development, troubleshooting and even one-off daily requests. AI
will bring them much needed help, backed by more knowledge and experience than
any single human could bring to bear”—Neil Kinson, Chief of Staff, Redwood
Software
“We
are still far from having a bonafide ‘smart home’ and the primary roadblock is
the lack of the essential link between sensing and action. Currently, we have a
variety of technologies that offer a compelling vision of the future, but that
vision is impeded by the fact that the devices are isolated, lacking context,
and are thus unable to act autonomously: the consumer must still supply the
intelligence for the ‘smart home.’ The mating of RF sensing technology
with mesh and other networking schemes will amplify the value of network
hardware, enabling them to provide powerful communications infrastructure and
sensory feedback—the necessary convergence of control and communications
needed to create cognitive systems. We will see this convergence entering the
market in 2019, led by forward-thinking tech players who will build out this
visionary ecosystem to satisfy the demands of consumers who want to see a
Jetson—esqe future, now.”—Nebu Mathai, EVP Product Engineering, Cognitive Systems Corp.
“As
AI increasingly takes on roles in the workplace, it will be judged not only on
its IQ, but EQ—emotional intelligence—and ability to perceive and understand
all things human. The ability to understand human emotions and
cognitive states will become part of the criteria for evaluating AI, as
companies make decisions on which AI solution to select for their workplace,
and even as consumers decide between systems like virtual assistants or smart
speakers to have in their homes”—Rana el Kaliouby, PhD, CEO and
co-founder, Affectiva
“The
focus of AI will shift from intelligence to empathy—we’re moving beyond the
point where basic intelligence suffices for consumer-facing AI, as customers
want to know that they are being viewed as individuals and not just as customer
data records. In 2019, vendors will focus more on increasingly
humanizing AI with empathy—including picking up on clues on customer
motivation, how they feel in the moment, how they act in certain situations,
and even what is happening around them”—Dr. Rob Walker, Vice President,
Decision Management and Analytics, Pegasystems
“As
businesses increase their use of AI to extract greater value from their digital
assets, metadata tagging will become an even more critical element of
enterprise storage. This will bring more attention to object storage, which
is centered on metadata, and the key will be integrating well with AI
tools”—Jon Toor, CMO, Cloudian
“Centralized
data will be replaced by a single view of all data. Data is coming at us
from different directions, at different speeds, and in different formats, and
controlling this tsunami is one of the key markers of empowerment and success
in the information age. Two massive trends are changing the landscape. First,
different vendors are coming together to standardize data models. Second, and
more important, is the emergence of enterprise data catalogs. These catalogs
are accessible in a hub, with one view of the entire federated data estate, and
deliver a shop-for-data marketplace experience. The more you share,
collaborate, and use the hub, the more valuable it becomes to the business.
Furthermore, it links your analytics strategy with your enterprise data
management strategy, as the data becomes analysis-ready”—Dan Sommer, Senior
Director, Qlik
“The
modern enterprise will continue to edge out technologies like Hadoop. The
merger of Hortonworks and Cloudera was a first look into the projected value
for Hadoop in 2019. Technology that was designed twenty years ago in an era
of ‘small’ data will no longer support the modern, global, and dynamic
enterprise. Data will still require management tools, but the complexity will
be eliminated with the rise of Artificial Intelligence and machine
learning”—Roman Stanek, CEO, GoodData
“High-profile
breaches this past year have thrust the application layer under the security
spotlight. As applications become increasingly sophisticated, their development
also opens up increased vulnerabilities. While DevOps is racing to keep up with
accelerated application development, it is becoming increasingly impossible to
manually keep up with, much less anticipate, threats. Machine learning
and AI will continue to be used to mitigate vulnerabilities much more
efficiently and with more accurate results”—Ivan Novikov, CEO, Wallarm
“2019
is going to be the year of open source AI. We’re already seeing
companies begin to open source their internal AI projects and stacks, and I
expect to see this accelerate in the coming year. The impetus for this is the
same as in other industries such as the cloud that have moved strongly to open
source—increased innovation, faster time to market and lower costs. The cost of
building a platform is high, and organizations are realizing the real value is
in the models, training data and applications. We’re going to see harmonization
around a set of critical projects creating a comprehensive open source stack
for AI, machine learning, and deep learning”—Ibrahim Haddad, Director of
Research, The Linux Foundation
“AI
will help elevate in-store customer experiences. AI will be used to help stores
elevate customer experiences and build loyalty in ways that were previously
impossible. When customers shop online, they often receive personalized
recommendations and offers. Retailers have tried in the past to use beacon
technology to enable the same level of personalization, but beacons are largely
considered a failure because they require specific app downloads, Bluetooth
connections or other factors that vastly limit their usability. This problem
will be solved by AI-trained face recognition algorithms. In 2019,
customers that opt-into face recognition programs will gain numerous in-store
benefits including personalized discounts, white glove service and shorter wait
times. Retailers will finally be able to offer customers the same level of
personalization in stores as online”—Peter Trepp, CEO, FaceFirst
“AI
will start to become embedded in many more enterprise applications, in
particular in applications for knowledge workers where AI and data analytics
will play an increasing role in supporting and even making decisions. At the
same time, the current misconception about all data analytics being AI
will be more widely discussed, particularly with regards to the availability of
sufficient, relevant and specific data to train algorithms and keep them
‘learning.’ This will lead to an increased focus on more advanced
methodologies that can learn and adapt based on actual real-time data”—Mikael
Johnsson, Co-founder, Oxx
“Because
companies are recognizing that AI cannot be built without high-quality data,
they will increasingly turn to specialized providers that sit on crucial data
resources to help them understand their unstructured data. For example,
Bloomberg is building NLP libraries that are specific to the financial
domain”—Gideon Mann, Head of Data Science, Office of CTO, Bloomberg
“In
2019 we expect a significant move forward with frameworks and standards for
measuring and testing bias in AI. We will see an increase in need for human
judgement and, consequently, an increase in these types of jobs, standards, and
protocols. My prediction is that momentum behind this will build as a result of
enterprises seeking to mitigate risk in the wake of high-profile scenarios of
things going wrong”—Jake Tyler, CEO, Finn AI
“The
traditional ‘break-fix’ approach to maintaining network quality of service
(QoS) is no longer enough. End customers are now so dependent upon always-on
connectivity and so sensitive to service outages that even short service
interruptions are now deal-breakers. Moving forward, we’re going to see
artificial intelligence (AI) emerge as the role of a fixer and optimizer to
enhance IT operations. Initial applications will tend to focus on security
functions, like DDoS attack mitigation and real-time automated path selection.
Eventually, uses will include AI-defined network topologies and basic
operations, which will help us forge a network that runs on auto-pilot”—Kailem
Anderson, Vice President of Software and Services, Ciena
“The
explosion of artificial intelligence (AI) within IT is poised to provide many
benefits and time-saving opportunities in 2019 but will require IT
decision-makers (ITDMs) to evolve into strategic consultants rather
than serving in reactive roles. AI will not replace the entire IT team
overnight, nor will it get close any time soon due to the current applications
of the technology. However, as AI starts to erode the need for humans in the IT
helpdesk, we will see those ITDMs that wish to survive do what they should be
doing anyway—grow, expand into higher value areas and maintain a close
relationship with the business. Failing to evolve into this strategic
leadership position will lead to ITDM’s extinction”—Ian Pitt, Chief Information
Officer,LogMeIn
“AI-powered
bank ‘tellers’ will become the norm. Bank branch consolidation will give
way to the next big trend—interactive kiosks. Using AI and data analytics,
these ‘tellers’ will deliver personalized experiences matching users with the
appropriate teller based on life-stage, transaction history and more. Many
banks have already seen success with virtual assistants in their mobile apps.
In 2019 we predict AI-technology will extend beyond the mobile app and 15
percent of banks will launch interactive kiosks”—Mike Diamond, GM of
Payments, Mitek
“AI
will get down to work beyond the hype and headlines. Practical AI will rule and
be focused on making shopping easier, patient engagement better,
lawyers smarter and cybersecurity stronger. We won't
see autonomous cars that never crash but AI will augment workplace productivity
in new and interesting ways in 2019”—Ram Menon, Founder and CEO, Avaamo
“2018
was the year of bots, and over the next year we’ll see pervasive analytics and
intent-based AI take this a leap further, highlighting the importance of
specialized service desks that streamline IT support management and allow for
instant knowledge delivery”—Phani Nagarjuna, Chief Analytics Officer, Sutherland
“AI
and machine learning (ML) have been the ‘silver bullets’ of the security
industry for the past few years. Malicious actors are taking note. For
instance, just like security vendors can train their ML models on malware
samples to detect them, malware writers can ‘train’ or tune their malware to
avoid detection using the same exact algorithms. Attackers can also poison the
data that ML models use in training. Because algorithms need massive amounts of
data to work, it can be difficult to weed out efforts to poison your learning
set with false information. We believe a significant attack or strain
of malware will leverage AI in 2019”—Nir Gaist, CTO, Nyotron
“AI
has the potential to impact the retail sector in a number of ways, but most
notably in 2019, we can anticipate increased product innovation in the
supply chain. As AI product innovations in the supply chain reduce overall
costs through risk mitigation, improved forecasting, sped up deliveries and customer
service capabilities, we can expect more and more companies to implement such
solutions, changing the face of retail in 2019”—Brad Taylor, Senior Director,
Engineering and Facilities, Radial
“Deep
Learning models have been shown to be vulnerable to imperceptible perturbations
in data, that dupe models into making wrong predictions or classifications.
With the growing reliance on large datasets, AI systems will need to guard
against such attacks data, and the savviest advertisers will
increasingly look into Adversarial ML techniques to train models to be robust
against such attacks”—Prasad Chalasani, Chief Scientist, MediaMath
“AI
will add an extra layer of predictability, allowing organizations to see
patterns and gain insights from IoT devices and past customer
behaviors—ultimately making supply chains smarter, leading to faster, more
efficient production and fulfillment, and happier customers. In 2019
and beyond, we can expect AI to take supply chains from reactive in nature to
prescriptive levels, helping companies get one step ahead of consumers’ rising
expectations”—Hala Zeine, President of Digital Supply Chain, SAP
“In
2019 AI will ‘cross the chasm’ in healthcare as mainstream
non-pioneering institutions apply AI-fueled clinical decision support tools to
everyday work, including radiologic analysis in the U.S. and oncology drug
selection in Africa and South America. Additionally, as advances in
molecular biology demonstrate that many ‘common’ diseases are actually clusters
of rare sub-forms, AI will find the high-value pockets of small data
(such as unusual genetic signatures) hidden in vast reams of big data”—Frank
Ingari, Board Member, Quest Analytics
“AI
for customer self-service isn’t as successful (yet) as the hype would
indicate. Many organizations in 2019 will take a split approach—more
aggressive use of AI to automate repetitive agent after-call work and a more
targeted approach with simple and high-volume self-service use cases”—Chris
Bauserman, VP of Segment and Product Marketing, NICE
inContact
“The
key word is cognitive load and how do companies reduce it by providing better
guidance and overall automation that helps make it easier to use—RPA (Robotic
process automation) is a great example of this and continues to heat up. As we
move into 2019, RPA will become even more disruptive in how industries like
retail, manufacturing, supply chain and even finance operate from the ground
up. In 2019, we can expect to see more widespread introduction of software
robots and artificial intelligence (AI) workers as organizations look to
leverage automation to enhance their overall commerce ecosystem”—Rob Maille,
Head of Strategy and Customer Experience, CommerceCX
“As
artificial intelligence applications grow in popularity, one key enabling
technology will be the ability to process larger data sets constantly being
updated with operational data. Fast access to not just historical data but also
current transactions and real-time inputs will be critical to delivering more
value to the enterprise. With the right data currency and quality, AI
will move from special projects into production”—Raghu Chakravarthi, SVP of
R&D and Support Services, Actian
“A
major hurdle in the customer experience space is users are still wary of how
brands collect, store, secure and use their information. Heading into 2019,
businesses should be looking to security in AI, using emerging technologies
as a way to protect their customers—both from a purchasing standpoint and from
potential digital threats that seek to steal the information customers are
sharing with brands”—Dan Kiely, CEO, Voxpro
“Intelligent
robotic process automation will emerge as business critical, as
companies will require the high automation level necessary to become
intelligent enterprises in 2019. Additionally, conversational AI will take
automation a step further to automate businesses’ customer support with more
intelligent chatbots. These two technologies combined are the next big
milestones to achieve faster, more effective and more intelligent AI”—Markus
Noga, SVP Machine Learning, SAP
“Artificial
intelligence (AI) will make it possible to remotely monitor our health and
automatically suggest lifestyle changes that could help prevent diseases or
spot them at the onset when they are much more treatable. We're already
starting to see this with FitBits reminding us to hit our daily steps or
diabetes technologies monitoring our blood sugar, but this is just the
beginning. In 2019 we’ll see an increase in health wearables hitting
the market that use AI to track a vast number of conditions like blood
pressure, painting a more holistic picture of a person’s health, as it changes
in real-time”—Kevin Hrusovsky, CEO, President and Chairman, Quanterix
“Many
AI-enabled automation projects in 2018 failed because they were targeting the
wrong processes to automate. In 2019, companies must assess what parameters
should be taken into consideration—things such as the number of users for any
given process, handle time and complexity (i.e. number of apps involved, type
of actions conducted etc.). If these elements are factored in, this will help
ensure that the processes being automated will yield a significant ROI for the
company. Automating the wrong processes will only lead to frustration
and halt an organization’s journey to successful automation”—Oded Karev,
VP, Head of Robotic Process Automation, NICE
“As we move into 2019, every telco operator in the
US will have a strategy defined, and budget allocated, toward monetizing
machine learning in operations. However, there is a shortage in talent that
will affect everyone and strain companies’ ability to deliver, unless they have
strong scaling strategies. There is a large pool of junior data scientists that
will be the key to addressing these shortages and will do so in the coming
years, but the learning curve will be felt in 2019. As a result of the current
knowledge gap, applications democratizing AI and ML will see a large
increase in demand but will likely fall short on their ROI due to
misinterpretation of data”—Johnny Ghibril, VP of Data Science &
Solution Architecture, B.Yond
“Machine
learning will continue to work pretty well but will suffer the occasional
ridiculous failure as the underlying statistical nature of many learning
algorithms becomes clear. A number of risks surrounding representation,
sensor tampering, state manipulation, priming, and catastrophic forgetting will
come (back) to light. Associated security issues will be fun to explore. On the
societal side, some inherent social norms exposed by AI/ML will continue to
shock. When machines learn from humans, they can pick up some bad habits and
some morally suspect habits. Who knew we were so terrible as a species?”—Gary
McGraw, VP of Security Technology, Synopsys
“Look
out for ontology-based data science projects to complement existing bots and
machine learning programs to round out the data science and AI approaches for
business in 2019, and to set the standard for how these tools can
drive the performance of workers in both efficiency and effectiveness.
Ontologies add an additional tool to the set of approaches that companies can
now deploy off the shelf and ontologies ability to link together diverse sets
of data and draw conclusions from them, make an ontology-based system an easy
start for enterprise and business organizations in 2019”—David Keane,
Co-founder and CEO, Bigtincan
“Enterprises have been so focused on the potential
benefits of AI, that it’s become more buzz phrase than reality. Rather
than focus on the buzz in 2019, businesses must focus on adopting AI
applications and projects that offer near-term value to their organizations.
To ensure success, they will need to put a plan in place, including identifying
the groups and tools that can actually pilot or incubate new AI technologies to
allow adoption enterprise wide. Gradual rollout after testing will help
mitigate any major disruptions to everyday business, while enhancing the
organization’s future technology footprint”—John Samuel, Senior Vice President,
Global Chief Information Officer, CGS
“We
will see a huge spike in the exploration and adoption of ML/AI tools that can
help develop mobile and web test scenarios without coding (codeless testing),
to speed up the process of code validation and to provide a greater stability
for the test code. These tools enable smart test recording with high degree of
stability that is a huge boost to organizational productivity and agility. On
the front of smart decision making and quality analysis, we will see
ML/AI solutions that can automate the slicing and dicing of data, and quickly
provide root-cause analysis for issues that were detected during the DevOps
pipeline testing activities”—Eran Kinsbruner, Director, Lead Software
Evangelist, Perfecto
“2019
will see an exponential increase in the number of research projects and
companies building solutions that leverage AI to increase developer
productivity. We expect that by 2020, all development will be assisted
by AI co-developers that understand developer intent, suggest next best
patterns and detect problems before applications go into production. This
will enable companies to continuously improve their digital experiences and
respond to market needs at a pace that was impossible before”—Antonio Alegria,
Head of AI, OutSystems
“Artificial
Intelligence will increasingly be used to detect bad actors targeting
employees’ and consumers’ inboxes (e.g. spam, phishing, etc.). As the
technology advances in the coming year, it will work pretty well for the most
part. However, its occasional mistakes will cause significant issues, like
financial and reputational damage, for businesses. Most users will find slips
in security utterly incomprehensible and security companies will have an
especially hard time explaining the matter to customers”—Nathaniel Borenstein,
Chief Scientist, Mimecast
“Enterprises
will focus seriously on data privacy initiatives to comply with EU laws (GDPR)
or state laws (e.g., CCPA) in 2019, but probably for less obvious reasons.
It is not so much the fines per se which can range up to 4% of global sales,
since it’s uncertain whether such hefty fines will be levied so early; rather,
top management and board directors are concerned about their fiduciary
responsibility to ensure that proper measures are taken to prevent such severe
fines, which could produce significant financial distress or reputational
damage. Separately, it should be noted that the usual risk-deflection method of
buying insurance against fines is not yet available in most countries”—Kon
Leong, CEO and Co-founder, ZL Technologies
“In 2019, the value statement of every vendor that
builds AI systems should focus on BOTH the value they wish to create AND the
underlying moral foundation of their service. How they collect data, with whom
they share that data, and what they end up doing with that data will
increasingly need a litmus test for what is acceptable and not. That litmus
test needs to be part of the culture of the vendor—it needs to come from the
inside out. While this will feel too ‘touchy-feely’ and constraining to some
vendors, it is absolutely necessary for long-term business viability to
establish trust credibly across their user communities. Without
transparency, there is no trust. Without trust, there is no data.
Without data, there is no AI”—Ojas Rege, Chief Strategy Officer, MobileIron
“2019
is the year that AI unlocks the tremendous value of productivity in the
industrial world. More companies are coming to market with vertical
solutions that require little know-how in training models or interpreting
results. This focused approach can be used by anyone, and enables very quick
time-to-value at large scale. This shift will increase productivity and safety
and will open the doors for new business models throughout the industry, like
Outcome-as-a-Service”—Saar Yoskovitz, Co-Founder and CEO, Augury
“The
biggest benefit of AI will turn out to be something that we think of as
quintessentially human: being ‘good team players.’ While previous years have
focused on individual algorithms doing things better than individuals, 2019
is about collections of algorithms starting to collaborate on complex tasks.
With their speed, absence of ego and built-in altruistic tendencies, the early
indications are that AI team performance will quickly outdistance their human
counterparts”—Timo Elliott, Innovation Evangelist, SAP
“AI offers healthcare a truly transformational
opportunity, particularly in the arena of virtual care. What we’ve known as
telemedicine is quickly becoming the analog past, while virtual care is
the digital future—the next iteration of the industry, and AI will play a large
role in this transformation. For example, complex algorithms can parse
patient information, helping to direct them to the most appropriate level of
care; natural language processing is advancing in a way that will make online
interactions simpler and more effective; and smart systems can gather patient
allergy, prescription history and health information to support safer and more
effective prescribing. Best of all, with these AI tools in the hands of
providers and healthcare organizations, the digital experience can enhance,
rather than supplant, the patient-provider relationship”—Jon Pearce, CEO and
Co-founder, Zipnosis
“2019 is the year where we have everything in our
hands to use digital technology; it will be the year that will differentiate
the laggards and the leaders, providing competitive advantage to the
forward-thinking organizations. The laggards still believe there is time, and
will keep developing solutions in silos, making small progress, without
realizing the pace of change is accelerating faster than in the last 20
years. The leaders are the ones that are set for digital transformation
across their organizations, and who will leverage Big Data and AI to deploy
solutions that fundamentally affect the full drug development life cycle;
they will reverse the current trend—growth of drug development timelines by
25%, reaching a startling 12 years on average—and bring much-needed therapies
to the market sooner”—Isabelle deZegher, Vice President, Integrated Solutions,PAREXEL
“In 2019, society will push for the demystification
of AI and demand a better understanding of what technology is being built, and
greater transparency into how it is being used. As transparency increases people will better
understand that AI is not an all-encompassing term for machines that can
replicate and act like a complete human, but rather a more explicit set of
functionalities that can better automate simple tasks and augment people
executing more complex actions. This will result in less fear of a machine
takeover and greater acceptance of new innovation”—Josh Feast, CEO and
Co-founder, Cogito
"In
2019 Artificial Intelligence (AI) and Machine Learning (ML) will nearly reach
its full potential by connecting and processing data faster over a global
distribution of edge computing platforms. AI and ML insights have always been
available, but possibly leveraged a bit slower than needed over cloud platforms
or traditional data centers. We’re already seeing this in the way airlines
build and service airplanes, government defense agencies respond to hackers and
how personal assistants make recommendations for future online purchases. This
year, thanks to AI and ML, someone will finally know if that special someone
really wants a fruitcake or power washer”—Alan Conboy, Office of the
CTO, Scale Computing
“2019
seems as if it will be the year of analytics, machine learning and AI.
These tools are already available, though their take up has often been
delayed by a failure to match these new capabilities with appropriate new
workflows and SOC practices. Next year should see some of the pretenders—those
claiming to use these techniques but actually using last generation's
correlation and alert techniques in disguise—fall away, allowing the real
innovators in this field to begin to dominate. This is likely to lead to
some acquisitions, as the large incumbents, who have struggled to develop this
technology, seek to buy it instead. 2019 is the year to invest in
machine learning security start-ups demonstrating real capabilities”—Stephen
Gailey, Solutions Architect, Exabeam
“Some
existing applications that we may see more than others in 2019 will be chatbots
and increasingly autonomous vehicles. The improvement in chatbot AI
capabilities, will create an opportunity for innovative customer service groups
to step up in 2019 over competitors. 2019 will also be a big year for
autonomous driving initiatives to leverage empirical data with continuously
improving algorithms and hardware processing power”—Scott Parker, Director
of Product Marketing, Sinequa
“As
AI and ML become mainstream, a new breed of security data scientists
will emerge in 2019. Preparing, processing, and interpreting data require
data scientists to be polymath. They need to know computer science, data
science, and above all, need to have domain expertise to be able to tell bad
data from good data and bad results from good results. What we have already
begun seeing is the need for security experts who understand data science and
computer science to be able to first make sense of the security data available
to us today. Once this data is prepared, processed and interpreted, it can then
be used by AI and ML techniques to automate security in real time”—Setu
Kulkarni, Vice President of Corporate Strategy, WhiteHat
Security
“A
top tech trend of 2019 will be the impact machine learning/AI on the quality of
software. In the past, we’ve designed delivery processes to be lean and reduce
or eliminate waste but to me, that’s an outdated, glass-half-empty way of
viewing the process. In 2019, if we want to fully leverage ML/AI, we
need to understand that the opposite of waste is value and
take a glass-half-full view that becoming more efficient means increasing
value, rather than reducing waste”—Bob Davis, CMO, Plutora
“Companies
will realize AI is an investment in the transformation of their internal
processes, not just a feature that can be turned on to magically fix inefficiencies. On
the vendor side, technology providers will make AI tools and platforms easier
to implement and put in place, and the difference between technology leaders
who can truly create this change within an organization and those who are
trying to capitalize on the hype will become more and more vivid”—Connie
Schiefer, VP Product Management, Mya Systems
“For
the last two decades, the epicenter of the world’s economy has shifted as
technology driven companies take over entire markets at the cost of businesses
like Sears. But that’s just the beginning. Big tech companies are already
beginning to use their advantages in AI and data to reach beyond their
traditional markets into entirely new ones. Amazon has its eyes on
entertainment and healthcare. Google is looking at the future of
transportation. No company is safe from AI driven disruption and we’ll
see this trend continue to accelerate next year. If companies are foolish
enough to be caught off guard, they’ll quickly follow in Sears’ footsteps,
unable to adapt to the new digital world where AI and ML reign supreme. The
hype around AI for automating everything will die down, though the urgency to
create more efficient processes will only increase”—Sudheesh Nair, CEO, ThoughtSpot
“2019
will be the year that artificial intelligence companies begin dismissing
efforts to modify broken hardware and processes. Instead, they’ll set their
sights on holistic ecosystems that reimagine and reshape the way we design
processes altogether. While the technological aspects of this process overhaul
will be what drives the necessary sea change, we’ll come to realize that an
even larger opportunity lies in using advanced technologies to optimize
human behaviors anywhere they intersect with business process flow”—Alan
O’Herliy, CEO, Everseen
“In
2019, we’ll stop doubting humans’ role in the fourth industrial revolution—nor
fear they don’t have one. It will become clear that the relationship between
machines and humans is not either-or, but rather, it’s highly symbiotic. We’ll
realize how crucial it is to marry human insight with AI in order to reach both
AI’s and humans’ potential. We’re already seeing that the AI solutions
succeeding at both the department- and enterprise-level are those that leverage
humans to set forth the larger strategic vision and drive the instinctual and
intuitive elements of any complex process. Solutions that are built to
capitalize on this give-and-take between man and machine will produce the best
outcomes and experience rapid adoption, as a result”—Or Shani, CEO, Albert
Technologies
“Most
early business AI applications have revolved around predictive and prescriptive
analytics, using AI to augment human decision making. In 2018, AI began going
deeper, not just forecasting but actually taking business actions. 2019
will see more adoption of deep vertical-specific AI that will
autonomously take high-value business actions across the supply chain—from
purchasing and warehousing to messaging and customer service management”—Fayez
Mohamood, CEO, Bluecore
“Almost
all software companies know every click that a user makes in their
applications. What's been missing is a true understanding of what the user was
trying to accomplish and whether they succeeded or failed. 2019 will be
the year that AI-driven technologies will begin understanding the difference
between user intent and basic software functionality. Armed with this
information, companies can target individual, team, and function improvement
efforts. And software companies can intervene proactively with customers who
are on the path to sub-optimal outcomes. Additionally, this will inform
software companies and their customers of the potential need for application or
business process optimization”—Michael Graham, CEO, Epilogue
Systems
“When
it comes to using artificial intelligence in recruiting in 2019, talent
acquisition teams will be adopting it with cautious optimism. While
organizations using AI earlier in the hiring process have seen promising
results, it’s clear that the technology is still in its early adoption phase
and AI is being used to inform better, faster and smarter hiring decisions, not
make them. However, we may see more widespread adoption of AI to reduce
the amount of time recruiters spend on mundane tasks so they can use their time
on more meaningful candidate interactions”—Kurt Heikkinen, CEO, Montage
“We
expect to see AI used more in higher education in 2019 as institutions continue
their digital transformation journeys and look to appeal to students’
preferences for adaptive, engaging learning experiences. Particularly necessary
Gen Z, universities and professors need to meet students where they are
at—online. As Gen Z is fully integrated with a digital era, their learning
preferences will reflect differently than generations before them. Using
resources with AI components such as AI teaching assistants, online courses and
writing centers will start to be used more frequently across campuses”—Kanuj
Malhotra, EVP of Corporate Development and President of Digital
Solutions, Barnes & Noble Education
“As
automated technologies shape the workplace in 2019, it’s important for
companies to think about how the onslaught of technology will impact their
company culture in the short and long-term. Many organizations are already
using AI to search for talent, but when it comes to other areas of the
workplace where employees will be encountering AI on a daily basis, companies
need to understand employee perceptions from the start. Before rolling out
any new technology platforms, businesses need to be prepared to communicate the
value the product will bring to the organization, how it will affect employees
for the better, and the positive impact it will have on productivity and
engagement. In doing this, companies will set their organizations up for
success when implementing new technologies”—Andee Harris, President, HighGround/YouEarnedIt
“We
predict artificial intelligence will become more prominent in the insurance
industry in 2019 as more insurtech companies and carriers utilize the
technology in their customer experience strategies. At the same time, we
also don’t believe that AI will replace the human insurance agent in the new
year or in years to come. Though machine-learning models can be used to help
agents become better advisors to their customers, the human touch will always
be important in insurance”—Jeff Somers, President, Insureon
“As
AI continues to be more prevalent, it is undeniable that automated
decisioning will replace traditional white-collar workers. This means AI
systems will be making the decisions instead of humans for anything from
approving loans or deciding whether a customer should be onboarded to
identifying corruption and financial crime. This is distinct from Robotic
Process Automation (RPA), which simply emulates human decisioning. Instead,
true AI systems will go beyond human capability. We can also expect to see
greater understanding in the boardroom about what AI really means—including
hard-nosed figures around competitive advance, reducing costs of operations and
removing headcount. Expect to see this C-suite understanding trigger issues
around unions and job security as a result of significant operational
changes”—Imam Hoque, COO & Head of Product, Quantexa
“While
smart virtual assistants and conversational AI will gain a lot of traction in
2019, a large focus of machine learning and its superset artificial
intelligence will be on understanding content. AI will be used to
filter out what is real and what is not, what is appropriate and what is not.
And while strides will be made in understanding content in that context better,
the bigger challenge is training data without applying biases. This catch-22 is
what makes this problem extremely difficult to solve, but one that will have a
lot of attention in 2019”—Sameer Kamat, CEO, Filestack
“Alongside
the increase in demand for AI within companies, we’ve also seen a continued
shortage of trained data scientists. To increase the adoption of AI, AI
platforms will need to empower traditional developers with tools to enable them
to create machine learning models faster, as well as ensure they have an
integrated platform that will allow developers to annotate and label the data
needed to improve the accuracy of their models”—Dale Brown, VP of Business
Development, Figure Eight
“The
biggest threat to US and Europe is the rapid advances in AI coming out of China.
China is undoubtedly an AI juggernaut and will completely outmaneuver the west
if we’re not careful. Why? Because the success of AI is tied to the
availability of massive amounts of organized data. In China, it is socially
acceptable to trade private, personal information, for small amounts of
monetary value / perks. For better or for worse, this gives companies who
operate in the country a massive advantage over companies here. If we want to
compete, we need a solution to the data problem, and fast”—Hanns Wolfram
Tappeiner, Co-Founder and President, Anki
“The
need for AI-enabled search and analytics solutions will become more prevalent
in 2019. Traditional search functions will give way to the emergence of
cognitive search, resulting in AI-driven solutions to help enterprises
un-trap their data and derive more valuable knowledge and insights. By 2020,
cognitive search will streamline information to the point of reducing reactive
searching by 20%--and organizations need to be ready for this in the year
ahead”—Kamran Khan, Managing Director of Search and Content Analytics, Accenture Applied Intelligence
“In
2019, we’ll see more organizations move to glass box AI, which exposes the
connections that the technology makes between various data points. For
instance, glass box AI not only tells you there is a new retail opportunity, it
also uncovers how that opportunity was identified in the data. It also provides
retailers with an opportunity to check their data—and any public or
aggregate data they pull in—to ensure AI isn’t making bad assumptions
under the adage ‘garbage in, garbage out’”—Nikki Baird, Vice President of
Retail Innovation, Aptos
“With
an increasing availability of Artificial Intelligence (AI) capabilities driven
by cloud computing, AI will make its way into video conferencing in
2019 in everything from meeting room activity analysis and efficiency,
understanding participants’ reactions to given messaging, automated joining
procedures, and platform utilization. As organizations seek to optimize
their services and work more efficiently, it’s only natural that AI, now
readily accessible to assist with predictive analysis and turning data into
actionable insights, will transform conferencing and collaboration as we know
it”—Jordan Owens, VP of Architecture, Pexip
“We
will in the near future see the lines between audio content and written content
disappear. All audio will be searchable in the same manner the text-based web
is today, and all text will be accessible as audio, with your favorite voice
(Artificial Morgan Freeman?) reading it back to you. As voice assistants and
search algorithms continue to advance, you will soon be able to have a
human-like conversation with your assistant, who has instant access to all the
knowledge in the world”—Johan Billgren, Co-founder and Chief Product
Officer, Acast
“In
2019, I predict that it will become clear that the information and analytics
systems that are on the bleeding edge of creating and policing
truth—particularly AI-based technologies—are themselves part of the ‘bias’
problem. This will lead to the start of a fundamental shift in how we
think about truth—not in binary terms—but as points on a spectrum, with
underlying information systems and analytics systems under fire for their
inability to either measure or enforce the integrity of their underlying data
sets and analytics methods”—Kris Lovejoy, CEO, BluVector
“I
expect 2019 will be the year we’ll see an explosion of production
applications leveraging artificial intelligence. The tools and models available
on the market are ready for prime time, which means it will be far easier for
companies of all sizes to deploy intelligent applications. Along with that,
we’ll also see further soul-searching and advocacy around what role firms
providing machine learning services should play in ensuring the ethical use of
their products. AI experts carry a great deal of clout in that conversation,
since the services ultimately won’t work without their help. It will be
interesting to see what norms emerge out of that process”—Blair Hanley Frank,
Principal Analyst, ISG
“For
enterprises, 2019 is the year early adopters of an AI platform strategy will
experience a leap ahead of their less innovative competitors. There will be
clear winners, and clear losers in terms of both market share and margin
growth. The investments made in automating data ingestion, and building machine
learning algorithms will kick into the high gear of self-learning.
It’s this phase—when ongoing patterns in data spur self-learning—that result in
benefits that start to scale across the whole organization”—Dr. Anil Kaul, CEO
and Co-Founder, Absolutdata
“Organizations
will experience further disillusionment with all the vague hype around machine
learning and AI. They’ll increasingly realize that accurate predictions
require not just a large volume of training data, but a particular
type—behavioral metadata. Analysis of this data can be mined to better
shine a spotlight on what’s used and what’s useful. This is the same
insight that drove Google Search’s ranking prowess two decades ago: the content
of a webpage was less predictive of its utility than how often other
pages—built by other people—linked to it. As the ML/AI buzz continues to wear
thin, we’ll see a strong appetite emerge for this type of impact-driven
technology and behavioral metadata among organizations”—Aaron Kalb, VP of
Design and Strategic Initiatives and Co-founder, Alation
“Last
year was the year of the data scientist—enterprises focused heavily on hiring
and empowering data scientists to create advanced analytics and machine
learning models. 2019 is the year of the data engineer. Data
engineers will find themselves in high demand—they specialize in translating
the work of data scientists into hardened, data-driven software solutions for
the business. This involves creating in-depth AI development, testing, DevOps
and auditing processes that enable a company to incorporate AI and data
pipelines at scale across the enterprise”—Nima Negahban, CTO and
Co-founder, Kinetica
“AI
will fundamentally automate the order-taking side of sales and empower
successful reps to become consultants to buyers, helping both parties
discover the critical resources needed to inform their buying and selling
decisions. AI-powered innovation will anticipate sales challenges and buyer
objections and extract insights to better predict success during the
buyer-seller engagement. In the post-sales phase, AI can pinpoint best
practices and identify factors affecting customer experience to help increase
both upselling and word-of-mouth selling. Finally, AI will rapidly
produce a more coachable, customer-informed sales rep who is smarter, nimbler
and better prepared to sell successfully”—Yuchun Lee, CEO and Co-founder, Allego
“Over
the next few years, AI will be increasingly used to dynamically modify
and serve creative content based on what’s relevant in a given context, for a
given audience. The goal and opportunity is to meet the audience where they
are—whether being served content in a browser, interacting with a physical
product and launching a digital experience by scanning packaging, or at home
conversing with branded content using a voice assistant. While creative teams
and designers will still determine the aesthetic and tone for a given piece of
content, their role becomes even more crucial as the designers of generative
frameworks, determining which elements in an experience to make flexible while
still maintaining the core of the creative concept”—Claire Mitchell,
Director, VaynerSmart
“While
2018 saw many retailers and brands gain more familiarity with AI and its
potential use cases, 2019 will see those applications put into practice. AI
will fundamentally change the way consumers interact with brands, and I expect
that to become abundantly clear in 2019 through new levels of
personalization. Brands that adopt the use of AI to optimize the
customer experience will see the implementation begin to impact their bottom
line”—Adam Goldenberg, Co-CEO and Co-founder, TechStyle Fashion Group
“Thus
far, the capabilities of AI have been zeroed in on solving the problems we
know—more efficiently extracting patterns and insights from massive data sets
we’ve always been familiar with historically. Next year will bring the
greater potential of AI into focus, demonstrating its capacity to digitize
things that previously couldn’t be digitized and introduce completely new data
sets that change the status quo and solve problems we didn’t know we could.
Video AI will be a great example of this, helping turn physical settings into
actionable data that companies in retail and other sectors can utilize to
strengthen customer experiences like never before—and unlock new services and
customer value they may not have even thought about bringing to market”—Michael
Adair, President and CEO, Deep North
“Personalization
has long been the holy grail for marketers and everyone agrees results improve
by knowing what customers care about and engage with. Today’s marketers
have more behavioral data than ever, but often don’t have the time, resources
or knowledge to properly use it to tailor their approach. In 2019, AI
technology will address this issue, ultimately benefiting customers and
business results. As marketers test machine learning, creative strategy will
need to evolve”—Cody Bender, Chief Product Officer, Campaign Monitor
“2019
will be a pivotal year for AI in the workplace—it will be the year we move from
conversation to impact. We’ll begin seeing AI integrated more deeply
into the day-to-day employee experience through things like digital assistants,
whether it’s voice, SMS or another channel. I think we’ll also see AI-based
digital assistants more front-and-center for new employees, taking a larger
role in processes like onboarding or skills training”—Gretchen Alarcon, GVP of
HCM Strategy, Oracle
"One
of the biggest challenges in translating lab performance into the clinical
setting is the ability to consistently replicate results over time, location
and assay—hence the need for rock-solid quality systems and standards that
provide quantifiable reliability over cohorts. As we move into 2019, we
are beginning to see real results on how we can apply artificial intelligence
to a traditionally painfully laborious and human-driven process that used to
take weeks and bring it down to real-time monitoring. When applied
properly, streamlining and expediting this process ensures that any variability
in the workflow—from the sample collection, processing, and all the way to
instrument ingestion—is drastically minimized and hence the results become
supremely reproducible, and where potentially actionable and clinically
relevant information is derived in mere seconds”—Aldo Carrasco, CEO, InterVenn
Biosciences
“Our
fascination with the use of computing power to augment human decision-making
has likely outgrown even the tremendous advances made in algorithmic
approaches. In reality, the successful use of AI and related techniques is
still limited to areas around image recognition and natural language understanding,
where input/output scenarios can be reasonably constructed, and that will not
change drastically in 2019. The idea that any business can ‘turn on AI’ to
become successful or more successful is preposterous, no matter how much data
is being collected. But the collection of data to support humans and algorithms
continues and raises important ethical questions and is something we need to
pay close attention to over the next few years. Data is human and therefore is
just as messy as humans. Data does not create objectivity. It is well
established that data and algorithms perpetuate existing biases and automated
decisions are—at best—difficult to explain and justify. Appealing such
decisions is even harder when we fall into the trap of thinking data and algorithms
combine to create objective truth. With greater decision-making power comes
much greater responsibility, and humans will increasingly be held
accountable for the impact of decisions their business makes”—Christian
Beedgen, Co-founder and CTO, Sumo Logic
“In
2018, we saw many examples of adversarial AI algorithms attempting to fool
humans, like Buzzfeed’s video of President Obama delivering fake sentences in a
convincing fashion. Soon we can expect to see this concept evolve into
a new class of cybercrime in which malicious content is automatically generated
by AI algorithms—a new category we define as ‘DeepAttacks.’ DeepAttacks
can manifest themselves at scale by generating code within malware files,
creating fake network traffic in botnets, or in the form of fake URLs or HTML
webpages. Next year, I expect hackers to deploy DeepAttacks more frequently in
an attempt to evade both human eyes and smart defenses”—Rajarshi Gupta, Head of
AI, Avast Software
“Concerns
about AI and privacy were a hot topic in 2018 – businesses are increasingly
seeking insights into their data through the power of AI, but in order to get
those insights, they must share the data with third parties. Ensuring data
privacy, and in turn customer privacy, is a challenge we must solve to realize
the benefits of AI. In 2019 we’ll see more solutions emerge to enable AI
applications while maintaining airtight privacy using cryptography. One of the
most exciting emerging encryption technologies is homomorphic encryption (HE),
which is a specific way of encrypting data so that third parties can operate on
the encrypted data and still use privacy-preserving machine learning techniques
to glean valuable insights. We’re seeing this technique emerge in discussions
at NeurIPS and in some public solutions already, such as Microsoft SEAL and
HE-Transformer, and expect innovations around AI privacy and encryption to
explode next year”--Casimir Wierzynski, Senior Director, Office of the CTO,
Artificial Intelligence Products Group, Intel
"AI
will make a huge impact on cybersecurity by increasing exponentially the
ability to detect rogue patterns and foul play, and in time will improve
significantly on human ability to analyse data effectively, which will lead
to even faster detection and response capabilities via machine learning. Being
realistic, however, it is not going to be possible for AI to eliminate security
breaches entirely. This is a classic case of the trade-off between the
acceptable rate of false positives (where a legitimate activity is blocked
because it’s erroneously assessed to be malign) and false negatives (where a
malign activity isn’t identified as such). To drive the false negative rate
close to zero, an unacceptably high rate of legitimate activities would have to
get blocked”—Richard Anton, Co-founder, Oxx
“In
the automotive world, leading automakers and component suppliers are
constantly looking for differentiation through AI, and as a result, there
is currently a major shift underway from the rigid hardware solutions
that started the AI revolution to more flexible, software-based
ones that can be easily tailored to customer needs. In 2019
and beyond, AI will increasingly exist on the edge, as concerns around
privacy, security and latency make edge-AI preferable over the
traditional approach that relies on centralized AI systems. Manufacturers,
however, are struggling with the consequences of adding AI to their
edge-based products, mainly due to the expensive, bulky and power-consuming
hardware required for running them. They’re seeking slimmer, battery
friendly, and more cost-effective embedded solutions. This is why we’ll
also witness a growing demand for more
practical AI that can be
mainstreamed affordably, without requiring massive hardware or cloud, and
without compromising on quality or performance”—Adi Pinhas, Co-founder and
CEO, Brodmann17
Retail
modularity based on data and AI-driven insights could literally lead to dynamic
rearrangements within the store.
This already happens to a degree with seasonal changes such as moving barbecue
items to prominent positions as summer approaches. But now it will be possible
for more granular changes. For example, the baby food and Hamburger Helper
moves to the end cap on Sunday-Tuesday, but chips and beer move to the end cap
on Thursday-Saturday. Roll away a couple of center-store fixtures on the
weekend to make room for the olive bar installation. Flip the store layout by
day of week”—Tony Rodriguez, CTO, Digimarc
“Artificial
and augmented intelligence will help address our nation’s mental health crisis.
According to the National Institute of Health, nearly one in five American
adults suffers from a form of mental illness. There are significant barriers to
seeking care, including stigma, affordability and access. In 2018, the U.S.
news cycle was dominated by high profile celebrity suicides, the constant
drumbeat of emotionally charged stories in the news, and divisive midterm
elections. That brought important conversations about mental health and
depression to light for many people, thereby reducing the stigma. AI
will be able to help scale access to qualified providers and make it affordable
for people to get the right level of care. Combined with technologies like
teletherapy and telepsychiatry, it will play an increasingly important role in
improving collaborative care. AI tools and data-driven algorithms will help
clinicians track patient histories, identify times of crisis, and provide personalized
care for individuals to reduce symptoms and improve outcomes”—Karan Singh,
Co-Founder, Ginger.io
“AI
will power cyberattacks more and more. In fact, it is reasonable to assume
that armies of AI hackers will have greater, faster penetration with
more automation, allowing hackers to achieve greater success executing
cyberattacks. Cyber defense must look to AI for the faster analytics needed
to find malicious activities. With machine learning and AI-driven response,
security teams can automate triage and prioritization while reducing false
positives by up to 91%. Enterprises will seek innovative solutions that enable
them to stay ahead of the next unknown threat”—Gilad Peleg, CEO, SecBI
“In
2019, AI technology will finally be able to help not just identify attacks, but
also provide evidence-based guidance on how security teams can and should
respond to threats. In many situations, AI will be able to respond
without the intervention of SOC teams at all. Because AI is constantly
learning, the technology is poised to stay in step with attackers ever-changing
tools and techniques. Overall, AI expedites the time from attack identification
to remediation by eliminating many of the challenges and burdens that have
traditionally slowed-down the process. The implementation of such AI-driven
technology will result in a major risk reduction for enterprises of all
sizes”—Eyal Benishti, Founder & CEO, IRONSCALES
“Machines
will begin to understand cause and effect—today, when machines (such as
chatbots and virtual assistants like Siri and Alexa) respond to us, it’s purely
based on correlations. They do not have an understanding of causation. But as
machines are getting more disparate sources of data, they will begin to better
understand the causal relationship between a large set of variables. As humans,
we learn about cause and effect over time through pure common sense. In
2019, we’ll see this come to fruition with machines as we collect and feed them
more disparate data sources that enable them to build conditional probability
distribution to understand the direction of causality”—Michael Wu, Ph.D.,
Chief AI Strategist, PROS