AI is like electricity when it was first introduced over a century ago: people understood its promise but didn’t know what to do with it.
That’s where companies find themselves today with AI technology: IT leaders know it will transform businesses, but don’t yet know how to implement it safely – or how to get the ROI from using it.
That’s how Deepak Sethdirector analyst at Gartner, describes the current AI landscape. His advice: companies should let go of their fears around the use of AI and involve their employees directly.
“AI on its own isn’t going anywhere,” Seth said. “It will transition from people talking about what AI is to what AI can do.”
IT leaders want to make AI like electricity: flip a switch and it turns on. But AI leaders still have a long way to go.
In the early 20th century, companies often hired chief electrical officers to power the workplace and revolutionize factories. Rules were introduced to protect workers against electrocution and other hazards. And over time, an entire industry blossomed around electrical engineering, Seth said.
Early hopes for AI are giving way to real-world challenges
AI is going through similar growing pains regarding the deployment of secure models, and early results have been poor. A majority of experiments – up to 95%, according to one study – have failed, although in some places successful projects are now taking charge of knowledge management, back-office functions and customer support.
“We still don’t understand how to best work with AI,” says Seth. “We still don’t understand how to build that team structure where AI is an equal member of the team.”
Companies are now moving past the hype and waking up to the consequences of AI sloppiness, underperforming tools, fragmented systems and wasted budgets. Brooke Johnsonhead of legal affairs at Ivanti. “The early rush to adopt AI prioritized speed over strategy, leaving many organizations with little to show for their investments,” Johnson said.
Organizations must now balance AI, workforce empowerment and cybersecurity while still formulating strategies. That’s where people come in.
A human-centered approach will ensure that “AI complements human ingenuity, while also educating workers on what tools to avoid and why certain guardrails exist,” Johnson said.
For most organizations, the focus should be on applying AI effectively, rather than building everything from first principles Matthew Blackfordvice president of technology at RWS.
AI introduces new perspectives, and the people who are already thinking carefully about these issues are often best placed to work with it. “Strong engineers are still thinking about privacy by design, security by design and risk,” Blackford said.
Leave frustrations and failed projects behind
Despite their frustrations with AI, many companies remain stuck in the innovation theater Joe DepaGlobal Chief Innovation Officer at Ernst & Young (EY). But others find real value in AI, especially in back-office functions.
EY, the global tax and advisory firm, has embraced the technology and now has 30 million documented processes internally and 41,000 agents in production. An AI agent called the EY tax assistant provides up-to-date tax knowledge to staff and clients; this is critical considering that there are approximately 100 tax changes per day worldwide.
AI is becoming less of a technical problem and more of an adoption hurdle, Depa said. “What we’re seeing more and more now is less of a technology challenge, more of a change management, people and process challenge – and that will continue to be the case as those technologies continue to evolve,” he said.
DXC Technology takes a similar approach, designing tools that allow human insight, judgment and collaboration to create value that AI cannot do alone, said And Greyvice president of Global Technical Customer Operations at the company.
DXC’s security center features an AI agent who acts as a junior analyst and handles basic work such as classifying alerts and documenting findings. “This approach helped us reduce research times by 67.5% and recover 224,000 analyst hours,” said Gray.
The company’s efforts have freed up human analysts to focus their expertise on higher-value work such as complex investigations and refining systems to deal with emerging cyberattacks, Gray said.
“The most successful companies that make this transformation will be the ones that embrace ‘good friction,’” he said.
Managing AI success: the paradox
As is often the case, early movers will have an advantage. But they’ll still have to figure out what to do with the productivity gains they see, Seth said. “For that competitive advantage to become a reality, I would still say the organizational culture – the people, the reward systems – needs to change,” Seth said.
Companies may have to accept that some of the AI gains will remain underutilized in the short term. AI can help employees complete their tasks in half the time and enjoy themselves at a leisurely pace. Alternatively, employees can quickly burn out from being given more work.
“If you try to fire them, you don’t have a good workforce anymore. If you leave them alone, why pay them? So that’s a paradox,” Seth said.
Success with AI will only be possible if companies care about people, he said. “Because when you do that, you keep the team’s morale high and they are more willing to try new things. [to] go on that journey.”
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