Top 5 Business AI Innovations and Trends to Watch in 2022

To weather the COVID-19 storm and navigate the rapidly changing digital world, businesses are adopting artificial intelligence at a faster pace. To help our clients sail through digital transformation and create artificial intelligence solutions that deliver on their promise, we took up the challenge to identify AI trends and innovations that will define 2022. Here’s what we found.

Factors Shaping AI Trends for 2022

• Economy growth drives enterprise IT spending. Nearly two years after the onset of the pandemic, the global economy could accelerate 5.6% in 2021. The United States, China, Germany, and South Korea are expected to recover to pre-pandemic GDP levels per capita by the end of this year. Subsequently, worldwide IT spending is projected to reach $4.072 trillion this year (an 8.4% increase from 2020). Regarding AI spending trends, half of the businesses surveyed by Appen are planning to invest anything between $500,000 and $5 million in AI projects (34% up from 2020). The global AI spending, meanwhile, could soon reach $83.5 billion.
• The global labor market sees a rapid change. Since Q4 2019, job openings in the United States have surged 33%, while the official number of unemployed Americans reached 8.38 million last August. The paradox could be explained by the fact that COVID-19 has changed multiple industries, such as travel, hospitality, education, and healthcare. The pandemic-related health risks and policy rearrangements have only aggravated the unemployment crisis. In the meantime, the demand for skilled IT workers has skyrocketed, reaching 26,800 new tech jobs in August in the USA alone (up from 10,500 jobs in July 2021). These factors could have a profound impact on artificial intelligence trends for the upcoming year.
• Cybercrime hits record high. Last year marked a drastic shift to online everything. Global eCommerce sales, for example, grew by 27.6% in 2020. The number of employees who use personal devices for work purposes has now reached 67%. And before the pandemic, only 45% of executives had regarded security as an integral part of their companies’ strategy. As a result, the FBI received 69% more cybersecurity complaints last year than in 2019. The USA officials estimated the damage caused by different types of cyberattacks, including malware, distributed denial of service (DDoS), and phishing events, at a whopping $4.2 billion. Could artificial intelligence innovations possibly help enterprises lead through the cybersecurity crisis?
• Enterprise struggle to implement AI at scale. Globally, businesses spent $50 billion on artificial intelligence projects in 2020. Yet, just 11% of AI adopters saw a sizeable return on their AI investments. One of the common reasons for such lackluster results is a failure to get a buy-in from the C-Suite and scale AI innovations across the enterprise. According to a survey conducted by Alegion and Dimensional Research, 78% of all AI/ML projects come to a halt between proof of concept (POC) and full-scale deployment.
• The environmental crisis is worsening. Recent reports indicate that Earth has already warmed by 1.1℃ compared to preindustrial times. The temperatures could further rise by up to 2℃ in the next 30 years, causing irreversible damage to agricultural land, forests, and biological systems. By 2050, climate change could wipe off up to 18% of the global economy’s total GDP. It’s high time enterprises leveraged AI advances to address climate change.
• National AI strategies emerge. As more economies recognize AI’s potential to boost growth, resilience, and productivity across public and private sectors, national artificial strategies are beginning to take shape. A total of 50 countries, including the United States, China, and the United Kingdom, have national AI strategies in the works. The US artificial intelligence strategy, for example, will focus on fostering and attracting AI talent, addressing the semiconductor shortage, battling cybercrime, and ensuring the country’s leadership in the artificial intelligence race. Through 2021, the Biden administration could pour $6 billion into artificial intelligence projects and initiatives, influencing AI trends for decades on end.

Business AI Innovations and Trends to Watch in 2022

1. ROI-driven AI implementation
2. AI-augmented automation
3. Rise of responsible AI
4. Use of AI in cybersecurity
5. Environmental AI innovations

AI Trend #1: More Companies Could Adopt an ROI-Driven Approach to AI Development

“Launching pilots is deceptively easy but deploying them into production is notoriously challenging… Although the potential for success is enormous, delivering business impact from AI initiatives takes much longer than anticipated.” 

— Chirag Dekate, Senior Director Analyst at Gartner 

Some of the common reasons for AI projects’ unclear financial outcomes include:

• Limited access to quality training data
• A lack of resources and skills to implement artificial intelligence at scale
• A tendency to overcomplicate things — for instance, by using deep neural networks where simpler yet highly effective machine learning techniques could produce similar results
• A failure to gain buy-in at the executive level and proceed to a full-blown project

Here at ITRex, we believe that one of the biggest artificial intelligence trends for 2022 (and the years after!) will be taking an incremental, ROI-driven approach to AI development.

The concept of ROI-driven AI engineering and deployment pivots on:

• Fostering collaboration between business and IT teams, which could help companies decide on the business outcomes of deploying AI innovations beforehand and ensure C-Suite support
• Selecting a limited number of use cases for an AI pilot while devising a broader implementation plan early on
• Upskilling existing IT teams and enlisting the help of experienced artificial intelligence companies — either for turnkey AI system engineering or data preparation tasks, such as discovery, cleansing, and labeling
• Utilizing a powerful combo of SaaS, open-source, and custom-made AI solution components to speed up development cycles
• Ditching vast piles of historical data, which has become less relevant since the COVID-19 outbreak, in favor of wide and small data; the former is aggregated from a variety of sources, while the latter is easier to interpret and delivers instant insights
• Learning from failures, retraining algorithms on new data, and creating a continuous loop for machine learning model redeployment

AI Trend #2: Enterprises Will Aim for AI-Augmented Automation

“Last year, IT spending took the form of a knee-jerk reaction to enable a remote workforce in a matter of weeks. As hybrid work takes hold, CIOs will focus on spending that enables innovation, not just task completion.” 

— John-David Lovelock, Research Vice President at Gartner 

In the pandemic-ridden world, the role of information technology has shifted from supporting business operations to delivering business value. This change has had a profound impact on AI innovations and trends.

A breakdown of AI use cases in business. Source

Fueled by 5G rollouts, more powerful computer chips, the diminishing sensor prices, and flexible cloud services, the convergence of robotic process automation (RPA), artificial intelligence, and the Internet of Things (IoT) technologies has become a viable reality. This powerful trio brings companies one step closer to AI-augmented automation and pervasive intelligence. 

From lightweight RPA robots that take over payment processing tasks in healthcare to self-checkout solutions that know precisely which items a customer has put in the basket, recent advances in artificial intelligence will help enterprises achieve resilience and significant cost reductions. Here are some stats to prove it:

• 80% of executives are currently accelerating their business process automation efforts (World Economic Forum)
• 25% of companies already use AI in workflow automation, while 51% of enterprises are planning to do so shortly (Salesforce)
• By 2023, 40% of infrastructure and operations (I&O) teams will use AI-augmented automation in large enterprises, freeing up IT personnel’s time for strategic work (Gartner)
• 66% of businesses have increased their revenue by deploying artificial intelligence systems (McKinsey)
• Through 2021, enterprise AI budgets have increased, with 74% of companies allocating $500,000 or more for their artificial intelligence projects, which marks a 55% increase from 2020 (Appen)

AI Trend #3: Responsible AI Takes Center Stage

“Responsible AI helps achieve fairness, even though biases are baked into the data; gain trust, although transparency and explainability methods are evolving; and ensure regulatory compliance, while grappling with AI’s probabilistic nature.” 

— Svetlana Sicular, Research VP at Gartner 

In their recent article for Harvard Business Review, David De Cremer and Garry Kasparov described AI-based machines as “fast, more accurate, and consistently rational,” noting, however, that present-day AI innovations often lack intuition, emotional intelligence, and cultural sensitivity. 

While end-to-end automation and subsequent workforce reductions are not yet among the artificial intelligence trends for 2022, governments will need to address the moral implications of artificial intelligence adoption in their national AI strategies, ensuring positive automation outcomes for all parties involved. 

When it comes to business AI, companies should focus on creating intelligent systems that explain the rationale behind their decisions and do not discriminate against people based on their ethnicity, age, gender, religion, or place of residence. Additionally, stakeholders need to clearly communicate automation benefits to get employees on board and encourage them to participate in AI deployment and training. 

These numbers indicate that ethical, responsible artificial intelligence usage will be one of the defining AI trends for the upcoming year:

• Through 2022, every company could have 35 AI projects in development (CIO, Gartner)
• 65% of companies cannot explain how their AI systems make decisions and predictions (FICO, Corinium)
• 78% of enterprises are poorly equipped to consider the ethical implications of using artificial intelligence (FICO, Corinium)
• Only 45% of businesses engage in ethical AI monitoring (FICO, Corinium)
• By 2023, all AI professionals will have to demonstrate a good grasp of responsible AI principles to secure a job (Gartner)

AI Trend #4: Artificial Intelligence Will Lead the Cybersecurity Revolution

“We’ve seen a lot of the ransomware attacks and what it’s done. And in particular, it has impacted business resiliency. It’s no longer the case of encrypted computer and, you know, Reimage, and carry on. It’s impacting massive amounts of business and costing hundreds of millions of dollars.” 

— George Kurtz, CEO at CrowdStrike Holdings, Inc.

Using intelligent algorithms for cyberattack prevention became one of the most significant AI innovations of the past years. Forward-thinking enterprises leverage artificial intelligence to detect suspicious traffic within corporate IT networks, identify malicious software programs, spot infected links in employees’ emails, and even model cyberattack scenarios based on vulnerability assessments. 

The trouble is, the other side (i.e., cybercriminals) can do the magic too. For example, hackers can now manipulate the data used for AI model training, causing adversarial attacks. Other AI breakthroughs in the cybercrime field include inference, which allows attackers to access sensitive data by reversing AI engineer systems, and advanced social engineering techniques driven by behavior analytics. Additionally, hackers may employ AI to pinpoint security vulnerabilities in corporate IT systems. 

To address these looming threats, companies looking to deploy AI innovations should closely monitor all the data presented to AI models, review real-world data used for model training, and build the elements of randomness into their artificial intelligence models. 

Below you will find several statistics shedding light on artificial intelligence trends in the cybersecurity domain:

• Over 51% of enterprises use artificial intelligence to detect cybersecurity threats (Capgemini)
• Through 2021, 30% of organizations have already fallen victim to adversarial attacks — compared to just 12% in 2020 (FICO, Corinium)
• Hacking, customer fraud, and data breaches have grown by 5–12% in 2021 (FICO, Corinium)
• Automated cybersecurity solutions could increase the global revenue opportunities by $5.2 trillion in the next five years (Accenture)
• Between 2020 and 2027, the global AI cybersecurity market could be growing at a CAGR of 23.6%, topping $46 billion by the end of the given period (Meticulous Market Research)

AI Trend #5: Artificial Intelligence Will Drive Sustainability in Enterprises

“We cannot reduce what we cannot measure. Corporations ‘ climate action does not match our ambitions: one of the main reasons is that corporations don’t accurately measure their climate impact and track it enough over time. Fortunately, tools and techniques to help us exist, one of the most powerful ones is artificial intelligence.” 

— Charlotte Degot, Managing Director and Partner at BCG GAMMA 

Through 2022 and beyond, governments and businesses alike could turn to artificial intelligence to reduce reliance on fossil fuels, combat deforestation, and cut CO2 emissions. And while green AI innovations are still scarce at national levels, we’ve seen several commercial AI deployments that assist businesses in achieving their sustainability goals. 

Google, for instance, coupled their data center cooling technology with deep learning and reduced energy consumption by 40%. And CO2 AI, a novel sustainable artificial intelligence solution by Boston Consulting Group, helps enterprises cut CO2 emissions by 30–40% by accurately measuring their carbon footprint and making intelligent recommendations. 

These numbers prove that environmental sustainability is one of the hottest business AI trends for 2022:

• Artificial intelligence helps companies reduce greenhouse gas (GHG) emissions by up to 10% (BCG)
• The use of AI for GHG emission monitoring could result in $208–424 billion savings for global companies in the coming years (BCG)
• Artificial intelligence could aid the world in achieving 93% of the environmental sustainability goals defined by the United Nations (Springer Nature Sustainability Community)
• The growing adoption of sustainable AI systems could create up to 38.2 million jobs globally (PwC)
• The economic impact of AI-driven environmental solutions could reach $5.1 trillion by 2030 (PwC)

If you need help navigating the emerging artificial intelligence trends or implementing AI innovations, please contact the ITRex team! Together you’ll build a brighter, safer, and greener future!

Also published here.