A recent Gallup poll showed 75% of Americans think AI will reduce the number of jobs over the next 10 yrs and 77% don’t trust organizations to use AI responsibly. That distrust of AI is a big challenge distribution executives face as they seek to deploy artificial intelligence in ways that employees will embrace and not resist.
It formed the backdrop for a session entitled “Combining human and artificial intelligence to build the next competitive edge” Wednesday at Distribution Strategy Group’s third annual Applied AI for Distributors conference in Chicago.
Or, as moderator Janet Zelenka said, the subtext for the session might be: “Oh my gosh, what about the people?”
Zelenka, the former CIO and CFO of distributor Essendant and Stericycle, a company the provides medical waste disposal services, said it was crucial that distribution executives address the people side of AI from the start, given AI’s far-reaching impact. “This is a change management exercise more impactful than anything we’ve seen so far,” she said.
Panelist Paul Kennedy, president and CEO, DSG Supply, an electrical, plumbing and HVAC distributor, agreed on the importance of communicating a company’s AI strategy to employees clearly.
“The most important thing a leader can do is create the narrative of how AI is going to evolve in your company, because otherwise the narrative will be created by what our employees are learning about AI from different sources,” Kennedy said.
Kennedy cited a discussion in an earlier conference session of how AI could reduce employee headcount by 50% in certain situations, the kind of scenario the Gallup poll shows many people fear. He said executives should lay out a vision of how AI can drive growth, by handling repetitive tasks people do today, freeing them up for more creative and strategic tasks.
“AI can take out 80% of the repetitive, low-value tasks of inside sales rep or customer service rep,” he said. “That allows them to look at exceptions and other higher-value activities they can spend their time on. The challenge is how do we redeploy that time we just found to drive growth?”
Executive misalignment on AI
One answer the panelists provided is that AI will not only change jobs but create new ones. For example, some companies are starting to look for chief AI officers, a job that’s not existed until now, said panelist Tracy Deuell, interim CIO, and vice president of IT, Bostwick Braun, distributor of industrial products, and managing partner of advisory firm CXO Partners. Zelenka observed that such AI leaders should be held responsible for the risks associated with AI as well as the benefits.
AI not only will give employees more time to innovate by eliminating tedious tasks, it should allow them to be more engaged with their colleagues, said the fourth panelist, Deana Stanton, vice president of global compensation at Kyndryl, an IT services company that was spun off from IBM in 2021. She said she uses Microsoft CoPilot, an AI application, to summarize meetings so she doesn’t have to take notes, allowing her to listen more carefully to what colleagues are saying.
Stanton also noted the big differences in how CEOs and technology leaders view employee attitudes to AI, as documented in a recent survey of 1,100 business executives in eight countries conducted by Kyndryl. The Kyndryl People Readiness Report found 73% of chief information officers and chief technology officers say most employees are embracing AI versus only 45% of CEOs, while 45% of CEOs believe employees are resisting AI compared to only 8% of the CIOs and CTOs.
The survey also found CEOs put more emphasis on hiring people with AI skills, while the tech leaders are more focused on providing current employees with the skills, they will need to utilize AI, Stanton said.
She emphasized that human resources departments have a significant role to play in redefining jobs as they change, including as more teams become “hybrid,” involving humans working with AI-driven bots. It will be HR’s job, she said, to write new job descriptions and come up with appropriate compensation.
Stanton predicted the proliferation of AI will lead hiring managers to put less emphasis on traditional degrees and more on practical skills and experience.
‘Why are you asking me this?’
The wide-ranging discussion raised several other important points:
- Panelists agreed that AI systems work off knowledge as well as data, and that distributors have many older employees who have accumulated a wealth of knowledge over decades of work. That knowledge that must be captured by AI systems to make them more effective. Among other things, which can help train new people brought on to replace those that retire. But Zelenka observed older workers may feel threatened when asked to disclose what they know: “They might say, ‘Why are you asking me to share this? That’s my reason for being here.’ That’s a conundrum.”
- As AI systems operate increasingly independently, how will companies deal with them providing customers incorrect information or communicating in an offensive way with an employee? “We currently don’t have a process around that today,” Stanton said. She said employees will have to be trained to monitor AI output and correct the underlying information and data AI draws on to prevent future errors. “That is a new and emerging role we’ll see on the horizon soon,” she said.
- As AI is more widely used, the metrics companies use to measure employee productivity will have to evolve, Kennedy said. “HR will lead that,” he said.
The session underscored that AI poses many questions related to employees. But in the question-and-answer period, an attendee came back to the question of AI potentially reducing headcount.
He said if a company doesn’t leverage AI to reduce employee costs and a competitor does, “you’re going to be the one laying them off.” “You better move now to use AI as a weapon,” he said, “or someone is going to use AI as a weapon against you.”
Kennedy responded that companies that don’t deploy AI early and use it to drive growth will have no choice later on but to use AI to cut costs. He said the important thing is to get started now, and not wait for perfect conditions, such as having data in pristine form.
“Try some things,” he said. “It’s an iterative process because the data will never be perfect. Make some bets and take some chances.”
But don’t take chances on what employees hear about a company’s AI strategy. That must be clearly articulated from the start, or they will assume the worst.
Don Davis, former editor-in-chief of Internet Retailer magazine and Vertical Web Media, is a freelance writer based in Chicago. His experience in retail and distribution goes back to his childhood when he worked in the toy wholesale business founded by his father and two uncles and in their discount department stores located throughout the New York metropolitan area.