12 Current AI Trends & Predictions for 2022/2023 According to Experts

Amid the lingering effects of the COVID-19 pandemic, artificial intelligence (AI) either promises unprecedented, sweeping solutions or threatens to supplant humanity in every imaginable way. We choose to focus on the first option, albeit with all the precautions about all the AI trends emerging from out of just about any lab furiously working to bring us the best artificial intelligence software.

Thus, we present all the crucial artificial intelligence trends that you should know. If you’re in business, these should give you ideas on how to navigate your own markets, especially given the effects of the pandemic in mind. If you’re a casual observer, the list should tell you how AI should figure in your personal and social spheres in the near future.

key ai trends

Pandemic or no pandemic, there is not any country that is not already touched by AI in any form. If you order from any online store, the product you are ordering is probably assisted on its way to production by some sophisticated AI-guided machinery. The website you are using is probably watched over by AI-enabled software, compiling all your actions so the vendor could get back to you with more offerings that are probably more than you bargained for in the first place.

The list could go on. You could see more of these developments in this AI statistics report, with the numbers to your satisfaction. Among others, it juxtaposes AI numbers with the COVID-19 effects on businesses.

As countries race for AI supremacy, so do their citizens, who see vast opportunities in the field for professional growth. In the years since the inception of AI, the US skills market, for example, is populated by talents covering just about every known sector of the field.

Source: Dun & Bradstreet

Against this background, we proceed to present the most crucial AI trends that you should take into account whether for business or personal reasons.

1. Minimize Uncertainty with AI

As far as organizations are concerned, the most sobering lesson of the pandemic is to be dynamically prepared for uncertainty. Next to that, they are wary of falling into the trap of investing in a stop-gap solution, which addresses only the issues related to the pandemic but fails to see the larger picture ahead. As it was, the pandemic left many organizations totally unprepared for the quarantines, lockdowns, social distancing, and strict sanitary requirements that governments enforced worldwide.

In particular, organizations had to rush setting up remote work software, while schools had to deploy distant learning management systems. Aside from these, they also had to factor in collaboration solutions, communication systems, project management platforms, and a host of other applications to minimize the pain of drastic transition.

It took the pandemic to make organizations realize how weak their technology infrastructures really were. They realized how holding off digital transformation before had exposed them precariously to the pandemic.

To be clear, even AI did not see the pandemic coming. But that is precisely the reason why organizations are now looking to have AI and ML set up in such a way that they could provide the crucial insight to prepare for the worst of times. AI and ML have already proven themselves capable of conquering difficult environments with just the rules as their initial input. The input is the key to preparing for uncertainty.

By deploying dynamic business operating models with the use of AI and ML, they could spot anomalies early enough to give them time to dynamically respond to the threats. And the figures speak for themselves: the share of organizations already reaping the benefits of AI has increased to 86%, while 25% of companies with widespread AI adoption expect to see the technology increase their revenues in 2021.

The pandemic revealed the value of AI in enforcing dynamic simulation modeling, workforce planning, and demand projection.

accurate forecasting to minimize uncertainty

AI to minimize uncertainty highlights:

  • The most crucial lesson of the pandemic is to be prepared for uncertain times.
  • The pandemic exposed the weakness of the technological infrastructure of organizations.
  • Dynamic simulation modeling with the help of AI and ML will help organizations deal with uncertainty better.

2. AI Ethics

AI doomsday scenarios aside, there are valid reasons why the increasing incursion of AI in all aspects of business, institutional, and personal activities is getting the attention of authorities, concerned organizations, and vigilant individuals everywhere.

One valid reason that quickly comes to mind is the spate of chilling reports of Apple, Google, and Amazon smart speakers listening to the conversations of their owners.

That’s not all. AI-powered toys and the companies behind them are similarly getting the flak for spying on kids.

And these are just for starters.

How about AI-powered financial institutions denying any of your credit and loan applications because of bias unwittingly loaded into the AI engines’ algorithms?

AI in the courtrooms

If you think that is creepy, then wait until justice systems start using AI to decide which among the populace deserve a vacation in some lovely jailhouse facilities from Socotra to Siberia.

AI is already showing up in courtrooms in the form of risk assessments to determine which one is at high risk of not showing up for court or getting rearrested.

Beyond the courtrooms, governments are waiting for the right time to introduce a wide-ranging array of facial recognition technologies to help them fight all sorts of activities against state and citizens alike. What’s not mentioned, of course, is how much of it can go wrong.

The threats mushrooming this early in the introduction of AI in many facets of life are keeping research organizations, advocacy groups, and think-tanks busy to write the future AI handbook of best practices, which is currently in a state of vacuum.

One could write up an entire book about the models emerging from these organizations and multiple committees. Exciting names are already out, like the Asilomar Principles and the more straightforward recommendations from the participating organizations.

No matter the number of principles that they could eventually come up with, it’s clear that AI needs to be stripped of human biases and preconceptions if it is to become the grand equalizer that many initially hoped it to be. Tainted AI is the last thing we would like to see running the world.

Build Ethical AI Economy

AI ethics trend highlights:

  • The absence of best practices and recent reports of privacy breaches are bringing together authorities and organizations to create the framework for the next iterations of AI.
  • Various AI principles are already in the works.
  • The issue of bias is one of the major causes of concern about AI development.

3. Quantum AI Around the Corner

On October 23, 2019, Google claimed that it has finally achieved quantum supremacy. While the term “quantum supremacy” smacks of some sinister AI networks taking over the world ala Skynet of the Terminator series fame, the use of the term to describe the event is nothing of the sort. It is, however, no less remarkable.

In the first place, what Google claimed to have achieved would mark a truly watershed moment in history: the first time that another computing system has broken ties with the Babbage and Turing computing paradigm. In practical terms, it simply means that another computing system has performed an operation that is not possible with traditional computers.

More specifically, the announcement indicated that the Google computing device—Sycamore—did in 3 minutes and 20 seconds what even current supercomputers could not complete in under 10,000 years. All that from just 53 qubits. Increase that to 60 qubits and so on and you get the idea.

Qudits looming

And while IBM and Google are squabbling over the announcement details, Purdue University has blazed ahead with what’s called qudit computing, which will be more powerful than qubit computers. With these advances in computing power, humanity is diving into Star Trek territory, and with AI added in the mix, there’s no more telling where the race is heading.

Source: Amazon; Science 2020

Quantum AI around the corner trend highlights:

  • The recent Google announcement of achieving quantum supremacy points to a time when quantum AI would take its rightful place among business and personal spheres.
  • Quantum AI will usher in tremendous possibilities hardly possible with current computing systems.
  • We are not even into full qubit computing yet, and another computing system based on so-called qudits is already in the works.

4. AI Hovers on the Edge

Edge computing is what big players like Google, NVIDIA, and Apple see as the solution to the centralized, server-side logjam plaguing networks, applications, and processes across industries.

In simple terms, the fix calls for businesses to simply install specialized AI chips on devices connected to servers. The solution, thus, not only relieves the servers of heavy workloads but also allows users to process information locally and instantly. On-device, real-time computing provides the kind of speed vital to the needs of modern businesses.

The setup confers the following benefits:

  • faster response time
  • reliable operations using intermittent connectivity
  • security and compliance
  • cost-effective solutions
  • interoperability between modern and legacy devices

Edge Computing Value and Use Cases

AI hovers on the edge highlights:

  • AI-powered edge computing is crucial in solving computing challenges.
  • These challenges relate to the Internet of Things (IoT), which integrates more devices than in the past.
  • Major corporations like NVIDIA, Apple, and Google are the leading investors in the technology.

5. Out of the Labs Faster

Companies bask in the successful use of AI in resolving multiple business hurdles. Now they are pushing the envelopes further by fishing AI solutions out of experimental labs and pilot stages to full production stages at a more rapid clip. Behind the scenes, it’s really AI pushing AI further. AI in the form of machine learning (ML) and AI-powered analytic engines help design more advanced progenies.

At the moment, this capability to rapidly deploy AI-enabled systems is mostly confined to large enterprises with the financial muscle to pull it off. Blending scope and scale, they are looking at the next three years to set everything in place.

These companies largely look to speed up the deployment of robotic process automation and AI/ML at scale across their enterprises.

How companies deploy RPA

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Source: KPMG

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Out of the labs faster highlights:

  • Large companies that have seen the power of AI are pushing AI solutions faster out from research labs
  • These companies are using AI-powered analytics engines and ML to deploy better RPA and AI/ML systems.
  • Large enterprises have set their eyes on the next three years to accomplish their goals.

Most Popular Artificial Intelligence Software

  1. Cloud Machine Learning Engine is a cloud-based predictive analytics modeling platform by Google, which can handle data of all sizes.
  2. Azure Machine Learning Studio is Microsoft’s AI engine that enables interactive data modeling.
  3. Salesforce Einstein processes data using Salesforce’s artificial intelligence.
  4. IBM Watson is one of the most well-known AI platforms that can predict trends and lets users discover business opportunities.
  5. Nvidia Deep Learning AI consists of a suite of AI products designed to accelerate machine learning.

6. AI Is Taking Over Hollywood

We have seen the power of computer-generated imagery (CGI) and AI push Alita the Battle Angel and Thanos punch their way to the box office. Still, even those are puny compared to what researchers are cooking up for the next AI role in Hollywood.

Forget James Dean coming back to life in a new movie. How about an AI algorithm nudging you to watch a current blockbuster that an AI has written, where robots performed all the scenes, fully helmed in turn by an AI director? If you think that’s too much, wait until you learn that another AI screened the scripts and suggested the studio buy the rights.

Multiple AI roles

These would be tremendous developments, but right now, AI has not really taken for itself these jobs the way it did factory workers and customer service reps. At the moment, AI has relieved animators of the need to hunch over thousands of frames or spend hours to render advanced visual effects. The animators simply moved on to more creative tasks.

In motion capture technology, humans and AI work together to achieve the best visual presentation. That’s Josh Brolin and Thanos, thank you.

Adobe and Kristen Stewart, meanwhile, just pioneered a novel neural network that can produce an impressionist painting.

AI impressionist painting by Kristen Stewart and Adobe

Fine-tuning the value of u let the team change how much the film resembled an impressionist painting. Image Credit: 2017 Starlight Studios LLC & Kristen Stewart via Futurism

Over at Disney, robot acrobats relieve human actors of the need to risk life and limb while performing gravity-defying stunts.

Beyond editing and performance, a Belgian company gives a foretaste of where things are heading further. Scriptbook, the company, says that its algorithm can predict whether or not a film will be commercially successful. All it needs to do so is to analyze the screenplay.

AI is taking over Hollywood highlights:

  • AI is extensively used in movie studios for multiple processes.
  • Motion capture is one of the most successful uses of AI in motion pictures.
  • New research points to AI getting a piece of predicting box office success for films under consideration, saving film studios on failed ventures.

7. Weaponized AI

The commoditization of AI tools has many countries and arms manufacturers racing to who could push the most powerful AI chip inside weapons systems. These include battle drones, war-class land, naval and aerial vehicles, surveillance systems, robots, and missiles, among others. Algorithms that once guide only business processes now help define best-in-class destroyers.

Nations stockpile autonomous weapons systems by the millions, prepared to release them under the right conditions. And much like various forms of malware, their AI-powered cyberspace cousins, they are ready to pounce and engage human targets without further intervention.

As the military units of countries try to outsmart their counterparts from other nations, especially those perceived as current or future threats, private companies are dragged into the stage. A case in point is when Google won the contract to apply its AI muscle to Pentagon’s AI initiatives, it split the population as it split the employees of Google.

In the larger scheme of things, the mix of players, combatants, technologies, and spaces in question can get so complex. At the last count, we could be looking at no less than 36 elements involved, each one already complicated in its own way.

Weaponized AI highlights:

  • Military installations are busy competing for AI chips for use in wars, current for future ones.
  • AI and algorithms are found in various military installations, surveillance systems, and weaponry.
  • Weaponized AI and algorithms involve complex elements to easily understand.

8. AI to Drive Better Process Discovery

Processes are the backbone of all business workflows. This is true no matter if the business manufactures cars or sells dolls. Many companies today rely on processes charted years or perhaps decades before. The use of AI will change all that.

Much like GPS allows Waze or other map-based platforms to chart the best route from point of origin to point of destination, the new AI-enhanced RPAs will use advanced algorithms to show businesses new ways of doing things in a much more efficient manner.

In the petroleum industry, the success of Shell Petroleum in employing AI in many of its operations and processes is well documented. As business forge ahead, many more are expected to follow in the footsteps of Shell Petroleum.

AI drives process discovery example

AI to drive better process discovery highlights:

  • Organizations will use AI to discover novel processes.
  • This approach will seek to improve processes and ROIs.
  • Shell Petroleum successfully used the approach to implement improvements in its operations.

9. Unbalancing the Competition

Much has been made of online stores and ecommerce establishments pushing physical stores to the brink of retail apocalypse.

In the face of the ongoing AI onslaught in almost all aspects of industries, a nagging thought emerges: how would this development unbalance the playing field between AI industries and non-AI industries?

It turns out Forrester has a quick answer to this: AI-driven organizations will steal $1.2 trillion per annum from their less-informed competitors. And growing at an average of more than 30% annually, they are on track to earn $1.8 trillion by 2021.

It’s not like the non-AI industries have not considered adopting AI too. What happened was that they simply missed out on how much of an impact any delay in AI adoption would cost them.

In specific terms, it’s about how 58% of businesses have considered AI technologies, but only 12% of them actually put AI into practice.

Along the same vein, we could look at how AI will profoundly impact industries, as depicted by choice industry samples in the chart below.

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Leading Drivers for Global AI Adoption in Organizations

Leading Drivers for Global AI Adoption in Organizations
Better customer experience: 50

Better customer experience

Leading Drivers for Global AI Adoption in Organizations
Improve employee productivity: 47

Improve employee productivity

Leading Drivers for Global AI Adoption in Organizations
Activate innovation: 45

Activate innovation

Leading Drivers for Global AI Adoption in Organizations
Speed up new product development: 45

Speed up new product development

Leading Drivers for Global AI Adoption in Organizations
Increase competitiveness/market share gains: 44

Increase competitiveness/market share gains

Leading Drivers for Global AI Adoption in Organizations
Improve risk management/amelioration: 42

Improve risk management/amelioration

Leading Drivers for Global AI Adoption in Organizations
Drive top-line revenue growth: 38

Drive top-line revenue growth

Leading Drivers for Global AI Adoption in Organizations
Higher margins: 37

Higher margins


Source: Statista 2020

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Unbalancing the competition highlights:

  • Industries adopting AI will profoundly impact non-AI competition.
  • AI industries stand to gain $1.2 trillion yearly at the expense of the non-AI counterparts.
  • The imbalance is mostly due to AI industries getting quick on their feet to apply AI in their processes.

10. Jobs Are Dead—Long Live Jobs

Much like how workers resented—and often reacted violently against—the mass production technologies of the Industrial Revolution, their modern counterparts are throwing wary eyes on the advent of AI in the workplace. For some of them, AI means job displacements all over the place, leaving them with no means to support themselves and their families.

Are their fears well-founded?

Jobs always tend to vanish, but pinning down the reasons for their disappearance is not always a straightforward affair. And in most cases, more sophisticated jobs that pay more and provide better working conditions actually replaced these jobs. Displacements are often temporary, easily mitigated by retooling and reorienting the affected workers.

AI jobs

In the case of AI, some jobs are indeed truly under threat, if not already totally on the retreat because of the technology.

Yet apart from the oft-repeated apprehension, not many share the gloomy sentiment. In particular, the World Economic Forum cites how the emergence of the internet raised similar concerns before, only to prove the critics wrong by instead contributing 10% to the US GDP. In the case of AI, 63% of CEOs are convinced that AI is poised to do more than that.

Before the pandemic, we noted how the US employment rate was at its lowest in decades. It was so that employees seemed happy to hop around jobs or freelancing gigs at will, to the dismay of employers who then had to dangle more incentives to attract job takers and keep them.

At that time, the supply of some skilled talents was so short that companies had no clue what to do about it. In April 2020 at the height of the pandemic, US unemployment skyrocketed to 23.08 million. This is a sharp increase from just 5.8 million in January 2020. Yet since May 2020, the number of unemployed started to slide down. By January 2021, it finally settled at 10.13 million unemployed Americans. Many attributed this recovery to industries and the government finally finding their feet dealing with the pandemic.

While these are impressive figures, they don’t take into account the fact that massive COVID-19 vaccinations have not even started yet.

Just before the pandemic, we also noted how 40% of organizations were adding more jobs as a result of bringing AI into their business. While the pandemic might have thrown a short-term wrench in that development, it is expected to pick up again. When it comes to AI, the dilemma is not about lost jobs: it’s how ready the job market and industries are to embrace this massive sea of change. To do so, they have to focus on reskilling and upskilling to meet the demands of the new market.

Finally, we also noted how the World Economic Forum predicted a “Robot Revolution “that would create 58 million more jobs by 2022. Again, the pandemic roughed up that projection. To adjust for COVID-19, the World Economic Forum came up with a new study. In its Future of Jobs Report 2020, it estimates that across 26 countries in 2025, 85 million jobs will be displaced while 97 million new jobs will be created.

AI creates more jobs

Jobs are dead—long live jobs highlights:

  • The increasing introduction of AI in the workplace makes workers fear displacement.
  • Research data, however, show the opposite: more jobs will be created in the long run.
  • Employers worry about the lack of AI-skilled talents.

11. Avatar World

No, it’s not about the alien tree-fangled world that James Cameron created. Instead, it’s about smart assistants taking multiple forms to help humans complete the tasks they have set out to do.

In specific terms, think about Alexa AI in the form of a sales agent aside from its popular speaker avatar in Echo. How about a Cortana walking interpreter or a Google Alpha Zero gamer? AI will transform into more human forms, so companies can encourage more customers to actually engage with them.

Disney World, for example, can start to transform its favorite characters as AI endowed avatars to help tourists go about the business of the entertainment centers. Samsung, on the other hand, is developing the Neon AI.  These are avatars programmed to “act as hyper lifelike companions.” The continuing advance of AI, natural language processing, computer vision, ML, and augmented reality all help to lay the groundwork for these developments.

One company spearheads this development. Artie, the company, allows gamers to interact with game characters using voice and computer vision. And it can easily extend the same technology for use in other businesses. One of their demonstrations, for example, showed an AI that can detect seven human emotions and around 80 objects.

Avatar world highlights:

  • Many industries will turn to AI-powered representations to enhance engagement and increase profits.
  • The gaming, entertainment, and software industries lead in the development of this technology.
  • The combination of AI, computer vision, improved natural language processing, and augmented reality makes this development possible.

12. 21st-Century Transportation

We are awash in visions of a totally AI-enabled autonomous transportation, from personal, business logistics, to public commute. Fleet management software solutions, for one,  already employ AI to manage enormous numbers of vehicles as they cover the planet from end to end. The visions have not fully materialized yet, but the next few years should see this trend shoot up in every direction.

Autonomous transportation brings with it more enabled smartphone applications to deliver smart vision into the road networks. Google Maps and Waze already own this space, but as with many business models, the market is that vast for a new player to emerge.

Also, 74% of executives fully expect to see smart cars on the road by 2025.

For global cities, AI brings a level of processing, control, and predictive capabilities that naturally make it a much-needed tool to contain the traffic blight that is wreaking havoc on their economies.

China and Germany are already laying the groundwork for such systems. Ahead, many more should follow with their own solutions.

Finally, AI should pave the way for safer roads in terms of detecting drivers who are under the influence of alcohol. The advanced analytical capabilities of AI could also allow it to pinpoint drivers who are texting while driving.

More tellingly, the technology already exists. For example, the new Motorola radio could do just that.

In conclusion, AI in transportation does not only mean intelligent autonomous vehicles but also safer highways.

How China Uses AI to Manage Traffic

21st-century transportation highlights:

  • The transportation industry stands to gain enormously from the application of AI.
  • Autonomous vehicles, for one, will be fully road-worthy by 2025, according to experts.
  • AI, in tandem with other technologies, should also make roads safer by detecting drunk drivers, among other things.

Expect to see and hear more of AI

Even with all the artificial intelligence industry trends covered here, there must be tens more going on from any part of the world as you read this article.

AI is just the tip of the iceberg, too, so to speak.

Machine learning statistics, for one, show a side of the latest technology in artificial intelligence that expands its possibilities even further.

As does this compilation of IoT statistics, which gives us a glimpse of devices as we will see them connected in more ways than one.

AI is going to be more pervasive ahead. There have been talks of some chatbot apocalypse, for example, pointing fingers at these code denizens taking over human jobs, similar to how we presented it in section 10.

And as we’ve shown, the fears are unfounded. In fact, AI promises more good things ahead—provided we keep the mad scientists at bay.



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Nestor Gilbert

By Nestor Gilbert

Nestor Gilbert is a senior B2B and SaaS analyst and a core contributor at FinancesOnline for over 5 years. With his experience in software development and extensive knowledge of SaaS management, he writes mostly about emerging B2B technologies and their impact on the current business landscape. However, he also provides in-depth reviews on a wide range of software solutions to help businesses find suitable options for them. Through his work, he aims to help companies develop a more tech-forward approach to their operations and overcome their SaaS-related challenges.

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