The artificial intelligence (AI) market saw a huge boom over the last 18- 24 months as many companies were forced to reimagine their technology usage in a fast-changing business landscape. By some estimates, 86% of companies said that AI had become mainstream technology during 2021. Additionally, AI strategies are expected to accelerate for 67% of organizations.
Further evidence of this growth is through AI democratization. While more people and organizations are using AI in new ways, user adoption needs to continue. There is still frustration among citizen developers and citizen data scientists to have easily accessible AI components. This will create opportunities for professional AI developers and citizen AI developers to collaborate and co-create.
Amid this rapid pace of innovation, it’s important to keep people in the process. AI should not be a replacement for people. Ideation and creativity are highly valuable in AI development and many use case scenarios. Without people involved to fine-tune, train, and test algorithms, the AI will create false assumptions, erroneous data, or infuse negative bias into the output.
Requirements for AI’s Sustainability
For many, it’s full steam ahead with AI as the only limit is creative ideas. However, others took a hard look at AI and realized it would be necessary to craft policies to provide governance and security regulations and guidelines.
The concern over data privacy led to the creation of the General Data Protection Regulation (GDPR)
in Europe. In turn, that led to the California Consumer Protection Act and similar regulations in other states soon followed.
So, what does this have to do with artificial intelligence?
Like GDPR, AI requires a set of checks and balances for long-term sustainability. Bad actors will always exist, but many organizations and governments are committed to using AI ethically for the good of humanity. Additionally, AI is dependent on the data behind it. Faulty or biased data would skew the AI models and take detrimental actions that could lead to irreparable harm.
Predictions for What’s Next
Yes, AI still seems like the shiny new toy that everyone is gushing over. Can it solve this? Can I create that? How do I use it? Do I need to be a developer? These types of questions highlight the need for continued education and simplification of use. Uncertainty still largely exists for many despite these same people using AI daily without knowing it (i.e., Siri).
On the other hand, new AI concepts are being developed that are pushing the boundaries of the possible in truly amazing ways. These concepts are becoming reality at a faster pace than before, and the pace will only increase.
Keeping all these things in mind, my predictions for 2022 in the enterprise AI space are centered around certain core themes that will be necessary for any future AI endeavors.
The Enterprise AI Impact Top 10
The Enterprise AI Impact Top 10 The companies on this list are strong leaders across the landscape of enterprise AI and are truly defining the category. Each one has set itself apart in multiple industries with scalability, capability, flexibility, and partnerships with customers and vendors alike.
So, which companies made Acceleration Economy’s Top 10 list? And what solutions do they offer? Check out the list below and dive into the overview of each company.
BONUS: To dig deeper into what’s impacting Enterprise AI and my take on these companies, check out the 2022 Enterprise AI Impact Report and Top 10.
Note: These companies are listed in alphabetical order.
This article appears in the Predictions 2022 Edition of the Acceleration Economy Journal  Download the Full Journal Here
