There’s a tremendous amount of hype around generative AI (‘GenAI’) at the moment, and much of it is likely to be justified. ChatGPT had the fastest adoption of any web-based service, and attention has now turned to the enterprise.

Microsoft has invested significantly to add GenAI features to Microsoft 365 and they’re not alone. There’s seemingly a new use case put forward every day, with a phenomenal amount of investment in time and money by tech companies large and small. Almost every vendor is adding some element of AI to their toolsets, whether it’s incremental improvements or whole new offerings.

One of the challenges is that ‘AI’ is now casually talked about in general terms, as if it’s one coherent whole. Which it’s not.

Functionality varies greatly, often built on top of entirely different AI platforms or engines, leading to very different opportunities and approaches.

To help make sense of this, Step Two has created an AI framework for the digital workplace, with the following aims:

• map out the landscape of AI capabilities that are focused on the digital workplace
• differentiate between distinct opportunities and use cases
• enable more meaningful discussion and planning around AI
• help teams to focus their AI efforts
• cut through the hype to uncover the more pragmatic reality

As always, Step Two’s approach is to focus on the underlying capabilities, not the products or vendors themselves.

What’s in scope for the framework

AI is starting to touch every part of our lives, and every aspect of how businesses operate. This framework focuses on tools and capabilities that that address employee needs and those of the broader workforce. Out of scope are the many business solutions that focus on customers and clients, such as chatbots that automate customer service (etc).

There’s also a consideration related to cost and resource commitments. This framework includes capabilities and solutions that range in cost from a couple of thousand dollars to perhaps a few million. Out of scope are solutions that range from tens of millions upwards to billions (noting that the ‘sunk cost’ of generative AI solutions already measures in the tens of billions).

So a solution that supports call centre workers in a bank is likely to be in the target price range, while AI used to identify fraudulent bank transactions is likely to be much more expensive, while being a tremendously valuable investment.

A living framework

Recognising that this space is innovating at a frantic pace, the framework (and the whitepaper) will be revisited and updated on a regular basis.

It’s expected that new use cases will be steadily added, although this will soon stabilise. Further paradigm shifts, by their nature, are impossible to predict.

Download the free whitepaper AI framework for the digital workplace to explore the framework, and start to plan with greater confidence.