2022 AI, Machine Learning and Data Trends to Watch

Just as much of 2021 felt like a repeat of 2020 in many ways, thanks to the ongoing COVID-19 pandemic, most IT trends to watch around artificial intelligence and machine learning will already be familiar. What is likely to change in 2022, however, is their roles in enterprises.

Read on for the top 2022 AI, machine learning (ML) and enterprise data predictions, as well as insight into potential challenges on the horizon.

AI/ML’s Buzz Continues

As has already been the case for several years now, AI and machine learning technology will be significant areas of interest and investment in 2022.

In 2021, 41% of companies accelerated their rollout of AI as a result of the pandemic, according to IBM’s most recent Global AI Adoption Index. A third of IT professionals now say their companies uses AI.

Adoption of AI at the edge is set to speed up this year, especially in the hospitality, entertainment, agriculture, manufacturing and transportation industries, said NetApp chief technology evangelist Matt Watts. “An explosion in ‘tiny machine learning’ chipsets for low-cost and resource-constrained devices, such as remote sensors that can collect and process data at the edge, will drive this trend,” Watts said. “These chipsets will fuel the ever-growing edge-core-cloud data pipeline, which industries will need to access and leverage to differentiate themselves in the marketplace.”

And for the buzz to continue, existing AI investments will have to scale and provide a return on investment. This year is likely to be a steppingstone in that direction, said Jonathan Grandperrin, CEO of software firm Mindee.

A move to an AI-centered model must be intentional and deliberate. “Software developers will need to learn how AI will fit within their own tasks,” Grandperrin noted.

The Ubiquitous Cloud

2022 AI investment is just one way cloud computing will remain vital for enterprise organizations.

Recent Amazon Web Services outages have highlighted a potential downside to ever-increasing cloud adoption. However, cloud adoption looks likely to expand in 2022, particularly as hybrid and digital workplaces develop and supply-chain issues delay traditional on-premises infrastructure equipment.

Certain organizations will see more efficient cloud transitions than others, including those that upgrade their IT networks and facilities to handle automation and advanced analytics, Watts said. “This transition will increase demand from businesses for visibility into their data -- how it is structured and where it is stored -- to ensure efficient use of compute capacity in the cloud,” he said. 

It’s also important to keep an eye on Kubernetes in 2022, noted Druva CTO Stephen Manley. “Customers want the flexibility of multi-cloud, while the cloud providers want to make their offerings as ‘sticky’ as possible,” Manley said. 

Organizations that want portability rely on Kubernetes for efficiency and simplicity. “All major cloud providers are either offering or promising to offer Kubernetes options that run on-premises and in multiple clouds,” Manley said.

Labor and Skills Challenges

Following the Great Resignation of 2021, hiring skilled IT workers will likely remain challenging this year. In its 2022 predictions, research firm Forrester prognosticated that enterprises will face a nearly 14% attrition rate for IT personnel. IBM’s 2021 Global AI Adoption Index found that a lack of necessary skills or expertise created the largest barrier to AI adoption for companies. 

“To retain talent and thrive through the shortage of skilled workers, organizations need to focus on training and education programs for current employees,” Wells said. In addition to hiring, IT managers can remedy labor and skills gaps by investing in low/no-code and AI technologies, he said. 

Data Security Remains a Major Concern

The rising threat of cyberattacks in the enterprise is expected to present a challenge this year. “In 2022, we will see a dramatic increase in both the volume and complexity of ransomware attacks,” Manley predicted. 

Ransomware is mainstream at this point, having become increasingly easy for criminals to use, Manley said. Attacks are also evolving. New tactics to gain environment control; avoid detection; exfiltrate data; and target virtual machines, SaaS applications and cloud-native applications will keep companies on their toes.

Security concerns will likely also lead to new regulations around 2022 AI/ML- and data-related activities. For example, given the massive expansion of AI adoption within the finance industry in 2021, ethical and security considerations are under a microscope, said Benoit Grangé, chief technology evangelist for cybersecurity firm OneSpan. “Policies and legislation pertaining to the use of artificial intelligence will lead to regulations in 2022 and beyond,” Grangé said.

Which 2022 AI, machine learning and data trends will you be closely watching? Tell us in the comments below!