The ultimate 2020 AI predictions list

by Max Smolaks
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A portrait of a techno-utopia that the next year could be

by Max Smolaks 31 December 2019

The year 2020 is almost upon us, and in the B2B technology press,
this means one thing: predictions. Hundreds of predictions from
dozens of vendors, containing all sorts of wishful thinking about
where their particular industry is heading next.

about quantum computing and predictions about the rise of the IoT,
about the skills gap and about 5G adoption. It’s a time-honored
tradition, as inevitable as mulled wine, dead trees and the guy in
the red suit.

as AI graduates from a research subject into a technology with
business applications and machine learning gets embedded into all
sorts of products and services, artificial intelligence is becoming
the new favorite of this annual prediction extravaganza.

But why not consume all of these predictions in bulk? Why not binge-read everything that the hardware and software vendors, service providers and consultancies expect to happen in the year ahead, all at once?

Here we have collected a total of 37 predictions about the state of AI and machine learning in 2020, and we’ve even arranged them in alphabetical order by vendor, from ABBYY to WWT.

likes listicles. Go on, enjoy yourself. Happy new year.

Max Smolaks, Editor

What they expect from 2020


Macciola, chief innovation officer:

and use of AI will proliferate

back to the beginning of this century when everything was touted at
Internet-enabled – as we begin this next decade, access to AI
enabling technologies will be everywhere and consumers will
experience AI without knowing it’s being used. For those who are
the owners of processes and customer experience, their access to
using AI will become more readily available.”

RPA and smart platforms

“RPA will become more integrated into ‘smart platforms’ that form the foundation for next generation intelligent automation platforms for handling more complex tasks or activities. BPM is still central to orchestration but these new intelligent automation platforms keep it simple by defining robotic routines that can handle narrow tasks or activities.”

robots will be more accessible and easily consumable

users will have access to internal marketplaces of robots or other
automation tools that are easy to configure and deploy on one’s
desktop. It becomes a central part of how employees get work done and
supports the rise of the citizen developer.”

marketplaces will take shape in the enterprise

“Similar to the explosion of marketplaces from the likes of the RPA vendors – UiPath and Blue Prism – enterprises will begin building out their internal marketplaces to create a way to share and reuse technology assets across the business.”

Accenture Technology

Kendrew, intelligent

year of transparency

will require that companies make transparency a reality. Consumer
demand for brands to be more open is clear. If they don’t pull back
the curtain on their business, they will lose trust and ultimately
loyalty. Data transparency is the hottest topic, for sure. It’s not
easy for businesses to do, but they will need to find ways to be more
open about the data they collect, how they use it, and how it impacts
decisions. They also need to show how they’re protecting it. Beyond
personal data, proving the provenance of products – from food to
clothes – and demonstrating ethical and environmental credentials
will all become more important.

“The reason more transparency will be really important in 2020 is because demand for it is growing, and the technology/tools are available, so we’re on the verge of someone being able to do it really well. Once one brand is able to redefine customer relations in this way, they will set the standard of expectations, and everyone else is instantly behind. And if they lag behind for too long, they might find themselves on the list of companies that couldn’t survive in the digital era.”


Stark, media

time for the BookAIs

“The gambling industry is going to face a massive tech skills shortage in 2020, as vendors battle one another for expert knowledge in Artificial Intelligence (AI). In-store bookies are going to be replaced by online and mobile gambling as we move into the new decade; AI will be central in this transition as vendors use it to interpret the customer data that allows them to innovate personalized experiences. But this process is about more than just tech, as AI only works with the right experts in place to interpret and refine the vast quantities of raw data. In 2020 we’re going to see bookies compete ruthlessly for talent, but also invest heavily into AI through CompSci graduate schemes and upskilling programs.”


Jewell, director
of product

to the

years we’ve heard about self-service analytics capabilities and how
they empower people to create insights and drive change. However,
descriptive and diagnostic analytics – finding out what happened
and why – is just the beginning. How do organizations address
high-impact, future-facing questions, such as predicting what may
happen next and prescribing the next best action?

“Historically these next steps in the analytic journey required data scientists with specialized model building skillsets. Yet, research shows there are simply not enough of these individuals to keep pace with the advanced analytics needs of an organization. Introducing self-service data science platforms and practices will enable a broader analytic workforce to up-level their skillsets, build models in a code free-way and become the heroes who will fill the data science talent gap and drive advanced analytics within organizations forward."


and IoT will drive new interconnection and data processing
requirements at the edge

“Equinix predicts enterprises will accelerate the adoption of AI and machine learning for a broader set of use cases, requiring increasingly complex and more real-time-sensitive processing of large data sets originating from multiple sources.”


Bray, VP EMEA:


companies will continue to shift toward AI-based solutions for
analysis of cybersecurity data. This is part of a broader trend of
companies shifting towards automation as workforce challenges, costs,
and security needs force them to consider tools that can automate
tasks efficiently and effectively. AI and ML tools will leverage data
– the new oil in cybersecurity – to augment or remove humans
using analytics.

industrial companies in particular are looking for ways to better
protect their critical infrastructure devices, whose vulnerability
has become more apparent in the past years given the growing number
and increasing severity of attacks on power utilities and
manufacturing plants.

“CISOs are hungry for tools that can help them with this problem and AI has the potential to flag anomalous activity that could point to an attack and analyze sensor data for more effective response to security threats and even predictive maintenance needs. Both of these are important because downtime in critical infrastructure environments can be catastrophic. AI is far from a silver bullet and requires extensive expertise and is still largely in early technical innings, but demand for it will grow in 2020 and beyond."


Ian Roberts, CTO:


is transforming every industry in which it is implemented, with its
impact upon the healthcare sector already saving lives and improving
medical diagnosis. However, the transformative effect of AI is set to
switch healthcare on its head, as the technology leads to a shift
from reactive treatments targeting populations to proactive
prevention tailored to the individual patient.

future is set to see AI-generated healthcare recommendations extend
to include personalized
treatment plans. An example of this in practice is the ability to
mitigate the risk of a person developing a chronic illness by having
the foresight to make changes in lifestyle choices ahead of
diagnosis. This medical understanding will be formed in part by their
own genome, combined with machine learning algorithms.

“To date, consumer personal genomics companies such as 23andMe are already helping to inform people of the need to manage their health; this ranges from avoiding coffee late at night to elevated risks of dementia and certain cancers. Currently we are in the infancy of AI in healthcare, and each company drives forward another piece of the puzzle and once fully integrated the future of medicine will be forever transformed.”

Insight UK

Gerdes, director
of digital


fears that it will replace human employees, in 2020 AI and machine
learning will increasingly be used to aid and augment them. For
instance, customer service workers need to be certain they are giving
customers the right advice. AI can analyze complex customer queries
with high numbers of variables, then present solutions to the
employee – speeding up the process and increasing employee

“Lufthansa for one is already using this method, and – with a faster, more accurate and ultimately more satisfying customer experience acting as a significant differentiator – more will follow. Over the next three years this trend will keep accelerating, as businesses from banks to manufacturers use AI to support their employees’ decisions and outperform the competition.”


Catlin, CEO:

will be involved in a major data breach

lives off of training data, and large collections of data lead to
data breaches. It might be medical, financial or just faces; private
or public sector, but some time in 2020 there will be a large leak of
personal data from an AI training set.”

will become a bigger part of RPA

Forrester and Gartner report that many RPA vendors are lagging behind
in supporting trending text analytics use cases, lack capabilities
with “unstructured document use cases” involving PDFs and have
trouble fitting text analytics/NLP components into their larger
environment. As companies automate larger and larger processes, NLP
vendors offering viable solutions that meet RPA requirements
– such
as on-premise/hybrid cloud options, easy-to-integrate APIs,
customizability and quick ROI
– will
rush in to fill the void.”

will arrive in the US

fears about automation stealing our jobs, the US has been
experiencing record lows in unemployment. 2020 will be the year the
massive recent investment in AI starts to show up in the unemployment
numbers. It will be a small effect to start, but presage larger
economic shifts to come in the latter half of the decade.”

biggest research advancements in AI will be theoretical

the last five
years applications of AI have run far ahead of our understanding of
how this all works. With some big practical advances in the latter
half of 2019, I predict we’re due for fewer world-beating
algorithmic inventions and more progress on the theoretical side
why any of this works. The field has been moving quickly, so by the
end of 2020 the balance will be shifting again with the theoretical
work paving the way towards a new generation of algorithms.”


the early 2000’s, “JibJab” had its moment as a cultural
phenomena allowing users to paste headshots onto animated dancing
bodies in flash videos. Expensive specialized hardware has thus far
consigned Deepfakes to the realm of enthusiasts, but 2020 will see
some commercial offering built around allowing anyone to inject
themselves into videos.”

will see a resurgence in popularity

2016-2017, chatbots were the future of business. But when the high
expectations met the technical brittleness of technology, the market
quickly cooled on the idea. Four
years later better NLP algorithms and a more mature technological
infrastructure means we'll start seeing some notable success stories
and enthusiasm will climb.”

will be a high water mark in AI acquisitions

the stock market at all time highs, large businesses will use pricey
shares to purchase technological advantages for the coming decade.
Many of these acquisitions will be a clear miss, leading to large
write-offs. But a few will completely shift the balance in various

magic and more solutions

will have a good year and will solidify its position as the defining
technology of the next decade. Providers seem to have wised up and
are no longer pushing the Magical AI angle, and are instead pushing
the correct message that AI can aid humans, making them faster and
better at their jobs.”

driving … still a long way away

“While AI in corporate settings will do really well, there will be a few spectacular failures of AI, most notably in the area of self-driving cars. Tesla’s new smart summon is quite impressive, but still has a way to go. It’s widespread use by the Tesla community will result in lots of videos of slow speed accidents where they run into cars, light poles and even people.”


Tee, CEO and founder:


techniques with which we are familiar today – such as neural
networks, event clustering, and regression – will be joined by less
familiar techniques such as topological data analysis (TDA) and
generative neural nets. TDA holds promise in commercial applications
because data has shape and shape matters. TDA maps the geometric
structure of datasets that are large, highly dimensional or noisy to
detect patterns and uncover insights. Generative models are trained
not only to recognize data but to generate new data just like it.
Generative neural nets can learn by recognizing novelty – data that
the model has never been trained to recognize.”

Whitehead, chief

for DevSecOps

organizations continue to adopt AIOps solutions at a rapid clip. SIEM
vendors are exploring how AI/ML technology can add operational
intelligence to their security event management processes. 2020 will
see these two parallel drives begin to intersect. AIOps tools will
begin to unify IT Operations and Information Security against the
explosion of next generation zero day threats. Both the challenges of
modern IT environments (i.e. multi-cloud, serverless, etc.) and
continued vendor innovation will fuel this trend.”


“2020 will continue the march of Artificial Intelligence and Machine Learning to mainstream acceptance in the greater IT industry. Even larger, typically more conservative enterprises will start to report tangible success with these technologies. As for smaller/midsize organizations, they will witness the weakening of past barriers to entry (e.g. cost, complexity), spurring more widespread AI/ML adoption. As a result of market maturity, proving measurable benefit will become imperative for all AIOps vendor solutions.”


Fairclough, VP services,
of the CTO (EMEA):

data will supercharge AI

are investing more in AI each year, as they look to use the
technology to personalize customer experiences, reduce human bias and
automate tasks. Yet for most organizations AI hasn’t yet reached
its full potential, as data is locked up in siloed systems and

“In 2020, we’ll see organizations unlock their data using APIs, enabling them to uncover greater insights and deliver more business value. If AI is the ‘brain,’ APIs and integration are the ‘nervous system’ that help AI really create value in a complex, real-time context.”


Versace, CEO and co-founder:

approaches to deep learning will make or break AI applications

approaches to deep learning can be tedious and time consuming due to
the need for massive amounts of data which need to be retrained over
and over again. Moreover, data is often not available online or is
confidential to one organization, so it cannot be combined with
others to create massive AI systems. In 2020, we’ll see the
emergence of new paradigms and approaches to deep learning to solve
these challenges.

example of a new approach to DNN is Lifelong-DNN: an approach that
reduces the data requirements for AI model development and enables
continuous learning in the cloud or at the edge to ease the AI
development process. With new approaches to DNN training,
organizations can build AI systems using their own data to bypass
issues of data privacy. As a result, enterprises and companies
looking to deploy AI solutions can leverage L-DNN for real-world
applications in visual detection, recognition and classification,
either using L-DNN alone or in tandem with traditional approaches to

will move towards the edge

“With AI and data becoming centralized, manufacturers are forced to pay massive fees to top cloud providers to access data that is keeping systems up and running. As a result, new routes to training AI that can be deployed and refined at the edge will become more prevalent. As we move into the new year, more and more manufacturers will begin to turn to the edge to generate data, minimize latency problems and reduce massive cloud fees. By running AI where it is needed (at the edge), manufacturers can maintain ownership of their data.”

Nlyte Software

Gaydos, CMO:

will keep the vital technology infrastructure underpinning society

next step in the future of AI for cloud services lies within the data
center and colocation facilities that power the public cloud and
major enterprise delivered online services that citizens consume.
Given the vital role that online services now occupy in the economy
and the lack of skilled technologists to manage the complex
infrastructure, the technology industry is heavily looking to unlock
self-healing infrastructures using AI.

“AI using machine learning and algorithms to learn from many inputs can evolve and improve with each new input. We will see significant advances in machine learning leading to smarter AI solutions since the more the models are used, the more they grow in utility value. The multiple uses, from ensuring service uptime through fault fixing and re-provisioning, to software that will rewrite itself to mitigate security any breaches or other faults without human interference slowing the process.”


Anderson, senior

boom in HPC infrastructure

enterprise AI projects graduate from “exploratory” to
“production” they will leave the public clouds for less costly
on-premises solutions, funding a boom in HPC infrastructure
build-out, but the requirements for that infrastructure will have
changed based upon their cloud experience.

clouds are great for learning and experimentation, but not for
high-utilization production operations. Public clouds will, however,
have a large influence on the next generation of on-premise
infrastructure that is built. The need for the lowest
time-to-solution, quickly taking action based upon the insights that
AI can give you, drives AI to push the underlying hardware (e.g: GPUs
and storage) as hard as it can go. But the simple truth is that the
cost of a dedicated resource in a public cloud is higher than the
cost of owning that resource.

“Another simple truth is that the value of AI is the computer deriving information that you can act upon from mountains of data. Add in the fact that AI has an insatiable need for growth of training data, and that public clouds have never-ending charges for data storage, and the costs climb. Put those simple facts together and it’s clear that production AI will be less costly if it is performed on-premises. The industry has become used to the extreme flexibility and simplicity of management that public clouds provide, and they will want to retain those characteristics in their on-premise solutions at the lower cost it provides.”


Ramani, chief


which means assessing the quality of a potential customer, is one of
the biggest challenges in the sales process. In 2019, we have seen
software in the form of chatbots begin to make the first contact with
leads and gauge the customer’s interest on behalf of the sales

Moving into 2020 we expect that chatbots, alongside other artificial intelligence solutions, will play a far greater role in aiding salespeople. Chatbots are just one example of how innovative technologies are reducing the burden of menial tasks for workers and enhancing their existing processes through AI-generated insights. In light of these benefits sales organizations, as well as those in wider industries, are increasingly recognizing that AI has the potential to reduce costs and drive efficiencies. In 2020, we expect that this trend will only continue as enterprises recognize how much technology has to offer their respective use-cases.”


Dean, CEO and

into the Digital Age

the last 60 years, the infrastructure sector has seen a zero percent
increase in productivity. This is surprising for such a crucial and
expansive sector
– with
only ‘fishing and hunting’ showing less innovation across the
same period. However, in recent years efforts to drive digital
transformation are beginning to yield substantial results.

like AI and Digital Twins have allowed these traditionally laggard
industries to drive efficiencies and drastically increase
profitability. Recent data suggests AI will increase infrastructure
sector revenues by £14bn a year in five years
– so
we expect its adoption to continue rapidly through 2020.

“The data also forecasts that four in ten infrastructure firms who don’t embrace digitization risk going out of business within the next ten years – so there is a strong incentive for the infrastructure sector to pursue digital transformation in the coming year."


Song, SVP and GM of security

actors will focus on AI and machine learning as a new attack vector —
sabotaging training data and disrupting decision-making

to see attempts to poison the algorithm with specious data samples
specifically designed to throw off the learning process of a machine
learning algorithm. It’s not just about duping smart technology,
but making it so that the algorithm appears to work fine — while
producing the wrong results.”

will uplevel the danger of social engineering

“In 2020, we expect social engineering’s role in cyberattacks to continue to rise, with the advancement of technologies like Deepfakes and its potential impact on the masses, and we’d be very surprised if a Deepfake attack doesn’t make the headlines in this US election year. The bottom line is that when it comes to cybersecurity, the human element remains a major threat vector.”


Oliver Muhr, CEO:

Human Intelligence with AI

in AI often grab headlines
– whether
it’s a robotic dog traversing a building site or a robo-caller
impersonating someone to book an appointment. Yet despite these more
outlandish examples, in a lot of ways we’re in a similar position
with AI as we were years ago: AI is more often than not simply
following a set of branching decisions. While the complexities of
those branches has admittedly grown, frequently what is called AI is
more accurately complex automation.

“In 2020, we will see a shift towards Human + AI. This type of Augmented Intelligence will empower people in organizations to make better and faster decisions by utilizing the wealth of knowledge from other team members and experts within organizations. Rather than taking in and retaining all information as equal, true AI will begin to mirror the way the human brain works – digging out what is important and forgetting less meaningful data. Real learning is based on recognizing when something you thought you knew has become obsolete and in 2020, the most advanced AIs will distinguish themselves through what they learn to forget, rather than simply what they taught.”


Goodenough, international

to the

transition of core business processes to the cloud has been the key
business-technology trend amongst organizations
for several years now. This is only expected to continue as more
marginal data workloads are discovered to make operational sense to
move off-premises. We saw in 2019 that business functions like CRM or
HR made that transition and this will accelerate as more big data
functions are able to make the jump. That being said, another trend
starting to develop in the second half of 2019 that we expect will
proliferate in the new year, is AIOps.

“The fundamental promise of AIOps is to enhance or replace a range of IT operations processes through combining data with AI. Like cloud migration, not only does AIOps have the potential to drastically reduce the cost of deployments, it can do so while improving performance. As organizations move into 2020 and review their business processes, it’s likely that one or both of these considerations will become a priority. For those that aren’t considering it already, they should prepare to start lagging behind their AI-enhanced competitors.”

World Wide Technology (WWT)

Locke, EMEA chief


2020 AI and ML will be at the core of every application with a user
interface. The hyper-personalization
of customer experiences will be on most companies’ agendas. They
will leverage applications to deliver highly personalized,
and relevant, predictive outcomes to end users. This means delivering
experiences which use new technologies to engage with a business’s
audience, for example, advertising on Spotify, through video games,
or in specific regions of a city.”

it health, shopping or advertising, every app that has a user
interface will have an AI element. The benefits for enterprise will
be clear, as companies are able to process data, and deliver results
at a scale that was simply unachievable before. AI will help to
correlate vast troves of information from different sources for use
in multiple use cases. 2020 will be the year AI and ML really begin
to deliver to users and enterprise.

this ‘hyper-personalization’
will be the proliferation of interlinked APIs. End users will be
delivered highly unique experiences, with truly individual pathways
between apps which in turn create unique outcomes. Enterprises will
be able to cross reference different, and vast, data sets to create
flexible models that will deliver the best return.”

rise of the ‘Chief Trust Officer’

has been a year of failing trust from the private to the public
sector, and there needs to be a huge swing to regain confidence.
Corporate mismanagement or abuse of data has been a topic of constant
media interest and consumers are increasingly aware of the
information that businesses hold about them. Customers in 2020 will
demand more transparency and will need to be sold on the benefits
they can reap before they feel comfortable sharing information with

in 2020, we will see companies prioritize
identity management, security and privacy. To help win back public
trust we could see the rise of the ‘Chief Trust Officer’ as
businesses seek to rebuild a trusting relationship with the public.
People will need to be given reasons to trust organizations.
Amid rising awareness of the value of their personal data, consumers
need to feel in control, and be given a return of significant worth.”

further secure personal data we will see blockchain technology, as it
matures, move from cryptocurrency to trusted content. This technology
can help with verifying and securing data. If it’s underpinned by a
blockchain hash it ensures the source is trusted and untampered.”

Maber, managing

the cashless society with AI security

march towards a cashless society will continue apace in 2020. As
countless new tech-driven financial services develop, consumer
financial data will grow exponentially, making it more difficult to
identify suspicious activity.

breaches have long displaced the classic “bank robbery” as the
biggest security threat to the banking industry. In 2020, we can
expect financial institutions to begin establishing adaptive security
systems to manage the ever-evolving threat of cyber crime.

and fintechs alike will begin adopting artificial intelligence as a
means of protecting both their assets and consumers. Due to the
quantity and the breadth of data circulated throughout the banking
industry, the use of AI is now a necessity to provide an additional
level of security by detecting suspicious patterns and automatically
taking steps.

threats, unusual network activity, or changes to a business’s data
will be analyzed in real-time and prevented. Technology like this
will allow banking security to be more agile, more capable of
managing larger volumes of data and free leaders to focus on broader
projects which drive business value.”

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