Optimizing AI's Impact Requires "Fundamentally Restructuring Workflows"

Wait! You mean AI isn't just plug and play? It can't take care of the hard stuff and increase profits without throwing off executive pickleball schedules? I want my money back!

We've been hearing variations on that theme since the few remaining graybeards still haunting offices from the dotcom era were starting their careers. And the lesson remains the same: to optimize returns from new technologies - including or especially AI - requires investment, turmoil, tough decisions and, yes, significant upfront costs. Because rethinking and reimagining how the enterprise functions is part of the price of scaling an ostensibly thermonuclear economic revolution. It doesn't just happen. That reality is also part of the reason why so many organizations are taking so long to adapt to and adopt AI. And why the costs are greater than the Silicon Valley hype machine promised. Smart businesses committed to realizing AI's opportunities are buckling up, taking their medicine and getting on with it. JL

Chip Cutter and colleagues report in the Wall Street Journal:

Business leaders risk missing out if their use of AI is overly focused on efficiencies. Maximizing ROI in AI requires a fundamental restructuring of business workflows rather than just adopting new technology. As adoption progresses from individuals to small teams to cross-functional groups, so do the returns on AI investment. To enable AI to scale across the enterprise, processes need to be redesigned. That’s less about tech than updating processes and social dynamics. Instead of thinking about it as an IT project, focus on the end-user experience. There are challenges: documentation hardly ever matches the reality of how work is done. Businesses are bogged down by rules and legacy systems. Redesigning a process with AI requires new checks and balances to ensure the effort doesn’t skew performance or lead to unintended outcomes. The line between those that make broader use of AI and those that don’t "will come down to their operating model.” 

Coinbase Global Chief Executive Brian Armstrong said his company was cutting 14% of its workforce as AI changes “how we work.” PayPal plans to cut 20% of its staff over the next two to three years, part of plans to step up its adoption of artificial intelligence.

Then there is Axon Enterprise President Josh Isner, who recently emailed the Taser maker’s more than 5,000 staffers and told them to essentially breathe: AI won’t trigger layoffs anytime soon, he assured them.

“I am thinking of AI as the thing that allows our teams to do more, not the thing that replaces our teams,” Isner wrote. Even if the technology lets staff be twice or even three times as productive, there will be additional problems to solve. So, he added: “Block out the noise and keep kicking ass.”

The message arrived at a moment of extreme anxiety in American corporations over how many jobs could be lost to AI’s powers to speed up and supplant much of white-collar work. Among executives making such decisions, a split is emerging: Use AI to shrink the workforce or stretch it?

Those diverging philosophies have been on display on earnings calls and in other recent announcements. Armstrong said Tuesday that Coinbase would eliminate hundreds of jobs as AI becomes more embedded in the cryptocurrency exchange’s operations. Staff will manage agents to do more of the work, he said.

LAYOFF TRACKER

Bed Bath & Beyond’s CEO told investors last week that with AI, “we’re going to experience significant reduction in head count.” Meta Platforms’ chief financial officer, Susan Li, questioned how many employees the social-media company would eventually need as AI is able to do more.

“We don’t really know what the optimal size of the company will be in the future,” she told investors last Wednesday. 

At the other end of the spectrum are companies that say they can keep head counts flat—not necessarily hiring, but not firing, either—by achieving more with existing teams. 

Spotify Technology co-CEO Gustav Söderström puts the choice companies face like this: They can translate productivity improvements right away into cost savings by trimming staff. Or, “the other thing you could do is to say we’re going to be roughly the same amount of people—we’re just going to do more.”

Spotify is doing the latter: “We’re keeping our head count roughly flat and just doing much more shipping, more value to consumers,” he said. 

Business leaders risk missing out if their use of AI is overly focused on efficiencies, said Nickle LaMoreaux, chief human resources officer at International Business Machines. International Business Machines CEO Arvind Krishna says maximizing returns on investment in artificial intelligence requires a fundamental restructuring of business workflows rather than just adopting new technology.

The use of AI within a company typically evolves from the individual contributor to small teams, cross-functional groups and ultimately the entire organization. As a company progresses from one stage to another, so do the potential returns on AI investment. That’s less about technology alone than it is about updating age-old processes and social dynamics, according to Krishna.

“In the next year or two, the enterprise world will sort into two camps: companies where AI runs their business, and companies where AI is still a project,” Krishna said.

The line between those companies that make broader use of AI and those that don’t won’t simply come down to technology. “It will be their operating model,” Krishna said.

IBM on Tuesday at its Think conference in Boston announced a slew of products and capabilities, including a new version of watsonx Orchestrate, a secure multiagent control plane, and IBM Bob, for securely building and deploying agents. 

While model developers are competing to stay one step ahead of each other, IBM is approaching AI from a different angle, helping its clients scale their AI efforts. AI is a core part of the technology giant’s strategy.

Last month, IBM reported higher first-quarter revenue of $15.92 billion and higher profit, driven by growing adoption of artificial-intelligence tools. While the numbers were ahead of expectations, the stock price fell. To some extent, that reflects the fact that IBM has been caught up in broader AI-driven concerns about software, but Ben Reitzes of equity research and consulting firm Melius Research has a buy rating on the company. “I’m excited…to see their AI-related business come of age,” he said. 

Client zero

The use of AI at many companies began in earnest in recent years with proofs of concept. The experimentation stage has led to the greenlighting of many projects. Now companies are looking to move to the next stage, or enterprisewide deployment of AI. That’s potentially more rewarding, but also much more complex from an organizational perspective.

Krishna cited the evolution of IBM’s internal human-resource processes as an example of the operating model behind enterprise-level scaling.

In the pre-AI era, Krishna said, if an employee requested an employment verification letter to support an apartment rental application, the workflow required up to 18 different human touchpoints, including a manager, an HR business specialist, back-office staff and multiple software systems.

Today, an employee can generate the letter by making a request to an internal bot called “Ask HR.” The AI agent, integrated into IBM’s security network, automatically verifies the employee’s identity, pulls the required data from the HR system and sends the letter. All the employee has to do is specify how the letter should be delivered. The 18 touchpoints have been reduced to just one, according to Krishna.

To enable AI to scale across the enterprise, processes need to be redesigned end to end, according to Krishna. IBM’s Project Bob, as the initiative was known internally before it became a product, was designed to manage the entire software development life cycle, from writing new code to patching old code, generating documentation, creating test cases and ensuring security compliance, he said.

“I don’t begin with eliminating steps. I begin with how many touch points can I take out? And how can I make it much more nimble and faster and end-to-end? That’s the goal. Out of that comes the fact that you should eliminate steps,” Krishna said. 

If people lose their jobs as a result, “I get to redeploy them, to do something else of more value,” Krishna said.

IBM has made progress rethinking its operating models, but more work lies ahead. 

The hard part 

Elevance Health Chief Digital Information Officer Ratnakar Lavu said AI is transforming the way the insurance giant works. The company, a longstanding IBM customer, is working with IBM to deploy AI-driven digital assistants. IBM said it is also one of the providers that helps Elevance with AI applications such as claims and approvals. Elevance works with other AI companies on a range of applications, too. For example, it has also rolled out an internal, OpenAI-powered tool called “Spark” to help its workforce operate at peak productivity. And it applies AI to the claims and approvals process.

Through a virtual assistant, the insured can ask complex questions about their benefits, such as whether knee pain treatments are covered, and receive instant, cost-optimized provider recommendations, according to Lavu. 

Like Krishna, Lavu said the successful deployment of such AI applications demands a careful recalibration of business processes across the firm. In his experience, that effort requires a deep collaboration between business and technology teams. And instead of thinking about the work as an IT project, the insurer is focused on the end-user experience. Rigorous AI governance that integrates bias testing, transparency and explainability are part of the effort from the start. As solutions are built and deployed, a parallel governance process takes place, making sure they perform ethically and within strict enterprise guidelines, Lavu said.

There are plenty of challenges along the way. Official documentation hardly ever matches the reality of how work is actually done. Businesses are bogged down by deeply embedded business rules and legacy systems. And redesigning a process with AI requires establishing entirely new checks and balances to ensure the effort doesn’t inadvertently skew key performance indicators or lead to unintended outcomes, Lavu said.

Those redesigned processes need to be connected to one another, too. For example, he said, the newly redesigned prior authorization process must continuously communicate with the newly redesigned benefits process. Only by connecting such end-to-end workflows can a company streamline operations, eliminate bottlenecks and see the full realization of AI investments, according to Lavu.

And while Elevance is seeing significant success and clear ROI in the redesign of the individual process around AI, the company “still has work to do in the connectivity of processes to see the net outcome.”

That’s the end-to-end connectivity approach driving IBM’s work. And while IBM has made progress rethinking its operating models, more work lies ahead, according to Krishna.

“I think it’s early days. We’re only a third of the way through what can be done,” he said.

“In your leadership discussions, are you having this idea of moving from AI to productivity to AI to growth?” she said in a recent interview. Though it is hard to predict how many people IBM will employ three years from now, “if I had a crystal ball,” LaMoreaux said, it would be “more.”

Yet some companies have more room to maneuver than others. At Meta, massive investments in data centers and other AI infrastructure are driving plans to lay off 8,000 people, about 10% of the workforce, CEO Mark Zuckerberg has said. Mass layoffs are also a swift way to boost the bottom line and a flagging stock price. Block and Snap shares both jumped following AI-related job cuts. 

About 80% of companies using AI agents, intelligent automation or autonomous technologies said they are cutting staff, according to a recent Gartner survey of 350 people in midlevel positions and above.

Coinbase’s Armstrong told employees that though there would be fewer staff, AI would allow them to get more work done. Getting leaner was necessary in a down crypto market, he said. Plus, the restructuring would better position the company for growth.

“Over the past year, I’ve watched engineers use AI to ship in days what used to take a team weeks,” he wrote to staff. “This is a new way of working.” 

Justin Briley, who was laid off Tuesday from his content-strategy and technical-writing role at Coinbase, questioned whether fewer employees would enable growth. “We were already pretty bare bones,” the 39-year-old said of his team.

Briley said he used AI to find efficiencies while working on the back-end of the company’s help website, and the technology allowed him to do more. 

“AI has been marketed as a solution to labor,” he said, though he predicts the technology will ultimately create “more work, not less.” 

At companies that say they are committed to keeping staffers, change is still coming. Many positions will look much different or combine the responsibilities of a few roles at once, human-resources specialists say. 

At Synchrony Financial, which issues credit cards on behalf of companies such as PayPal Holdings, Sam’s Club and Lowe’s, human-resources chief DJ Casto said he was already coaching employees to prepare not for layoffs, but for “redeployments” to new assignments. In some cases, they might be permanent shifts; others could be just for a few months.

Synchrony Financial might redeploy some employees to new assignments as a result of AI. JOSE A. ALVARADO JR. FOR WSJ

“We’re going to have to be a lot more agile,” Casto said. “I talk about this openly in our workforce: We’re going to have to be a lot more comfortable that it’s not going to be so black and white.” 

At Axon Enterprise, some managers say their teams have anxiety about potential job cuts, Isner said. Axon makes software in addition to security products such as Taser and body cameras, and its shares have fallen roughly 30% this year on investor jitters that AI could fuel a software apocalypse.

In his note to staff, Isner said that the company’s business remained strong and that people would still be necessary even in an AI world.

“My guess is we will still need a bunch of hires,” he wrote.

If anyone is in doubt, he told them, just browse OpenAI’s careers page. “There’s like 800 job listings,” he said.