The ultimate 2020 AI predictions list

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.

Predictions 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.

Now, 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.

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

Max Smolaks, Editor

What they expect from 2020


ABBYY

Anthony Macciola, chief innovation officer:

Democratization and use of AI will proliferate

“Think 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.”

On-demand robots will be more accessible and easily consumable

“Business 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.”

Internal 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

Emma Kendrew, intelligent engineering services lead:

The year of transparency

“2020 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.”


Akamai

Thomas Stark, media manager, EMEA:

It’s 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.”


Alteryx

Nick Jewell, director of product strategy:

Self-service data science to the rescue:

“For 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.”


Equinix

AI 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.”


Forescout

Myles Bray, VP EMEA:

Analyzing your security data

“Industrial 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.

“But 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.”


Healx

Dr Ian Roberts, CTO:

Empowering decision- making in health

“AI 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.

“The 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

Felix Gerdes, director of digital innovation services:

AI will augment humans, not replace them

“Despite 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 confidence.

“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.”


Lexalytics

Jeff Catlin, CEO:

An AI training set will be involved in a major data breach

“AI 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.”

NLP and text analytics will become a bigger part of RPA solutions

“Both 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.”

Moderate technological unemployment will arrive in the US

“Despite 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.”

The biggest research advancements in AI will be theoretical

“For 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 explaining 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.”

Personalized Deepfakes

“In 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.”

Chatbots will see a resurgence in popularity

“In 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.”

2020 will be a high water mark in AI acquisitions

“With 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 industries.”

Less magic and more solutions

“AI 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.”

Self 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.”


Moogsoft

Phil Tee, CEO and founder:

New AIOps techniques

“AI 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.”

Richard Whitehead, chief evangelist:

AI for DevSecOps

“DevOps 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.”

AIOps gets real

“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.”


MuleSoft

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

Unlocked data will supercharge AI

“Businesses 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 applications.

“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.”


Neurala

Max Versace, CEO and co-founder:

Customizable approaches to deep learning will make or break AI applications

“Traditional 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.

“One 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 DNN.”

Manufacturers 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

Mark Gaydos, CMO:

AI will keep the vital technology infrastructure underpinning society online

“The 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.”


Panasas

Curtis Anderson, senior software architect:

A boom in HPC infrastructure

“As 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.

“Public 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.”


Pipedrive

Vinay Ramani, chief product officer:

A helping hand in prospecting

“Prospecting, 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 teams.

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.”


SenSat

James Dean, CEO and co-founder:

Bringing construction into the Digital Age

“Over 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.

“Technologies 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.”


Splunk

Haiyan Song, SVP and GM of security markets:

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

“Expect 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.”

Deepfakes 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.”


Starmind

Oliver Muhr, CEO:

Augmenting Human Intelligence with AI

“Advances 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.”


Unravel

Justyn Goodenough, international area VP:

Moving marginal workloads to the cloud

“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)

Dave Locke, EMEA chief technology adviser:

AI driven, hyper-personalized experiences

“In 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 omni-channel 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.”

“Be 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.

“Deepening 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.”

The rise of the ‘Chief Trust Officer’

“2019 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 businesses.

“So 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.”

“To 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.”

Sarah Maber, managing consultant:

Protecting the cashless society with AI security

“The 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.

“Data 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.

“Banks 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.

“Insider 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.”