Businesses lack AI strategy despite employee interest — Microsoft survey – Computerworld

Generative AI (genAI) tools are becoming more common in the workplace, but business leaders are concerned that their organizations lack a strategy to deploy the technology across their workforce.

That’s according to a Microsoft survey of 31,000 employees in 31 countries, published in the company’s annual Work Trend Index report. 

The survey indicates strong demand from employee for access to genAI tools. Three quarters of respondents use the tools in their jobs, the report claims, double the usage of just six months ago. Employees say AI saves time, enables them to focus on more important tasks, allows for more creativity, and lets them enjoy work more. And more than three-quarters (78%) of office workers use their own AI tools —  a phenomenon known as bring your own AI (BYOAI).

Business leaders also see potential in the technology, with 79% of leaders surveyed believing AI use is needed for their organization to remain competitive. 

Microsoft itself has claimed several large-scale deployments of its own Copilot genAI assistant: Amgen, BP, and Koch Industries are among the enterprises that have purchased over 10,000 “seats” of Microsoft 365 Copilot, CEO Satya Nadella said during the company’s recently quarterly financial earnings call. 

But not all large businesses are keen to dive in quickly, however. The survey found that 60% of leaders believe their organization’s leadership lacks the vision to roll out AI across their workforce. 

“While leaders agree using AI is a business imperative, and many say they won’t even hire someone without AI skills, they also believe that their companies lack a vision and plan to implement AI broadly; they’re stuck in AI inertia,” Colette Stallbaumer, general manager of Copilot and Cofounder of Work Lab at Microsoft, said in a pre-recorded briefing.

“We’ve come to the hard part of any tech disruption, moving from experimentation to business transformation,” Stallbaumer said.

While there’s clear interest in AI’s potential, many businesses are proceeding with caution with major deployments, say analysts.

“Most organizations are interested in testing and deployment, but they are unsure where and how to get the most return,” said Carolina Milanesi, president and principal analyst at Creative Strategies.  

Security is among the biggest concerns, said Milanesi, “and until that is figured out, it is easier for organizations to shut access down.”  

As companies start to deploy AI, IT teams face significant demands, said Josh Bersin, founder and CEO of The Josh Bersin Company. Deploying genAI tools puts the onus on IT staff to ensure data quality and security standards are in place, as well as “getting up to speed on the European AI Act, implementing governance, and helping to standardize on vendors and tools, if possible,” he said. 

With all this groundwork required, it’s likely to take a year or more for businesses to develop a comprehensive strategy around genAI, said Bersin.

Does GenAI generate business value?

Another sticking point is determining value and ensuring a return on investment when investing in AI.

AI takes many forms, but genAI is the focus of most newer AI initiatives within organizations, according to a recent Gartner survey. The most common way employees interact with the technology is when it is embedded into existing productivity and line-of-business apps (34% of respondents), such as Microsoft’s 365 Copilot, Adobe Firefly, and many others. 

Other ways to interact with genAI, include prompt engineering (25%), training bespoke genAI models (21%), or using standalone generative AI tools, such as OpenAI’s ChatGPT or Google’s Gemini (19%).

These genAI features don’t come cheap. In most cases, digital work app vendors charge an additional fee for generative AI features within their paid products. This can be as much as an extra $30 per user each month for Microsoft and Google’s business-focused AI assistants, while those with a more limited focus can charge less, such as Slack AI, which costs a not-insignificant additional $10 per user each month. 

Alongside the challenges in measuring the impact of genAI, spending significant sums in training up employees can also be seen as a risk. 

Demonstrating the value of AI projects is cited as the biggest obstacle to AI adoption, according to the Gartner survey. “As organizations scale AI, they need to consider the total cost of ownership of their projects, as well as the wide spectrum of benefits beyond productivity improvement,” Leinar Ramos, senior director analyst at Gartner, said in a statement.

Microsoft’s survey paints a similar picture. The majority of leaders (59%) are unsure of their organization’s ability to quantify any productivity gains from employee use of AI.

“Cost is really where organizations are getting stuck,” Milanesi said, with companies unsure of what returns they can expect when deploying generative AI. 

Bersin said many organizations have seen productivity improvements in early trials of genAI tools, but a shift to broader, company-wide deployments requires greater consideration of the value it can deliver. “When it comes to massive purchases across the enterprise, I am sure there will be lots of discussions about ROI, because these tools are expensive,” he said.

In its report, Microsoft cited a six-month, randomized control trial of 60 Copilot customers involving 3,000 workers. Results included an 11% reduction in emails read and 4% less time interacting with them, as well as a 10% increase in the number of documents edited in Word, Excel, and PowerPoint. The impact on the number of meetings was less clear; some companies saw an increase, others, a drop. 

There’s a tendency to focus on time saved when assessing genAI tools, said Milanesi, but that might not be the best approach. The real value is in improved quality of work and increased worker satisfaction, she said.This drives “better engagement at work and, in turn, better work,” she said.

Where a tool boosts employee engagement, cost becomes less of a consideration. “Think about the cost of a worker quitting, or someone staying in the job and not being engaged,” she said.

It might be that some AI tools are better suited to certain job roles than others. “The question for any leader is to identify what level of AI is right for the talent. Like for PCs, not everybody needs the top of the line,” said Milanesi.