Presented by BCG
Executives want to harness the massive potential of generative AI, but many are getting closer to the threshold. So far, only 6% of companies have managed to train more than 25% of their workforce in gen AI tools, and two-thirds of executives surveyed I think it will take at least two years for AI and the AI generation to surpass the hype.. Many boards and management teams are cautious and asking the big questions: How does this technology work and how will it change the way we do business?
“We are now entering a phase where companies are focusing on ways to make a real impact,” says Matthew Kropp, CTO and managing director and senior partner of BCG Consulting Group. “We see clients making big decisions and spending millions of dollars to achieve big goals with the goal of changing the way their business operates. Even though we haven’t seen much added value at the bank, we’re getting there.
But mastering the technology itself is only one part of reaching the potential of the AI generation. Organizations recognize that Generation AI is more than a tool that can be handed to employees as if asking them to install a Microsoft Word update. Rather, it is an opportunity to think about where and how generative AI can transform an organization and how work gets done. This requires breaking down processes, functions, and employee roles into their constituent parts to understand where and how generative AI can replace drudgery while augmenting and improving valuable human labor.
But it also means addressing the second point – and it’s not a trivial one: the major cultural shift needed to transform potential employee resistance or fear into enthusiasm. Adoption of AI is difficult, in part because it is simply so new and most people have not yet learned how to work effectively with these tools. But not only that: employees must to want use them and want to learn how to use them effectively.
“As companies begin to experiment, with the goal of solving problems and having real impact, they will begin to encounter employee resistance for many reasons.”
“As companies begin to experiment, in an effort to solve problems and make real impact, they will begin to encounter employee resistance for many reasons, including resistance to learning new ways work or simply refusing to use new technology that they believe is coming for their work,” Kropp says.
Identify business potential and gain employee buy-in
From the top down, every company will have some big opportunities, Kropp says, but that may not be the place to start.
“If you run a giant call center, this is a big opportunity to make that call center more efficient. If you’re spending billions of dollars on marketing, you have a big opportunity to streamline the way you create content,” he explains. “But there are also thousands of small opportunities in everyone’s daily work.”
To find these opportunities, you need to involve the entire organization by educating them, which is key to managing this type of cultural change. For example, giving them access to tools like Enterprise ChatGPT, training them on how to use it, and encouraging them to think about how to rethink their work.
“Employees must believe that the end goal is to improve their work in ways that actively increase the joy they feel in their work, their talent and skills, and make them happier in their role. »
“It takes basic ideas: people who get excited about the possibilities of technology, realizing that they can lighten their workload, while still giving them the time and space they need to delve into the parts of their job that they really enjoy,” he adds. “Employees must believe that the end goal is to improve their work in ways that actively increase the joy they feel in their work, their talent and skills, and make them happier in their role. »
AI and gen AI tools deployed in the sole pursuit of productivity ignore employees and their needs. But research by BCG Managing Director and Senior Associate Debbie Lovich and her team at BCG’s Henderson Institute shows that employees who love their jobs are 49% less likely to say they would consider taking a new job.
“Focus on reducing employee work and maximizing joy. Examine the employee’s work processes and determine what they do and what parts are painful or unsatisfactory. This is what you automate.
“So we have to reframe,” says Kropp. “Our recommendation is that you focus on minimizing employee work and maximizing joy. Examine the employee’s work processes and determine what they do and what parts are painful or unsatisfactory. This is what you automate. But humans can never be replaced when you need creativity, diversity of thought, risk management, relationship building and much more – the interesting and engaging aspects of the job, and these are very human aspects that technology will never be able to support. »
For example, one of BCG’s clients, a financial institution with more than 12,000 engineers, is implementing GitHub Copilot, a generative AI tool that can both write code and help engineers code. During deployment, they don’t just focus on basic training and best practices to use the tool effectively. They also demonstrate how the tool eliminates many tedious parts of the job while retaining the more rewarding parts of the job. hands of engineers.
“Generative AI is really good at writing test code, and engineers are really excited about it because they realize they can spend more time on the creative and problem-solving part of their job,” says -he. “They’re actually starting to see that this doesn’t replace me, it allows me to operate at a higher level. This allows me to add more value. It allows me to think more creatively. This allows me to do more fun things and less of the things I don’t like to do.
Integrating Joy into Future-Oriented AI Strategies
BCG developed the ADORE framework as a roadmap for successfully implementing AI while increasing employee well-being. It can be used by the organization as a whole, to transform a function from end to end, or by a single team wishing to change its processes and operations.
A: Aim for results. The first step is to articulate precisely what you want to achieve by integrating AI into a business process, whether that’s improving customer satisfaction, reducing costs, or increasing sales time.
D: Status quo diagram. Once you have identified what you hope to achieve, you map out each step of the process you are targeting from start to finish.
O: Optimize for AI. Here you look at each step of the process to identify which ones are work and which ones are joy, or in other words: which parts of the process can and should be redefined with generative AI and which things should stay between human hands?
A: Rethink the process. Once you have identified the strengths of generative AI that will add value to a process, you can rethink it. This may involve automating part of the workflow, or rethinking and rethinking the entire process from the ground up.
E: Guarantee results. Here, the right metrics are put in place to measure results and ensure that you achieve the goals and see the results set at the beginning. It’s also important to measure things like employee adoption, productivity gains, and the level of joy employees get from their work.
Why experimentation is always essential
Large-scale use cases like call center efficiencies and accelerating software development are just the tip of the iceberg, Kropp says. For example, we are seeing the transformation of AI-driven knowledge management, which started as a chatbot layered on top of a vector database. Today, knowledge management can synthesize insights from proprietary data present in all facets of an organization.
“You need to keep digging deep to find these opportunities and ways to engage employees in the lasting, positive change that AI represents. »
Meanwhile, engineers learn new ways of working, supported by code-generating agents. Biopharmaceutical companies are dramatically reducing the length of R&D cycles to accelerate drug commercialization. Insurance companies are using Generation AI to dramatically speed up the underwriting process, while consumer product companies are creating new direct-to-consumer sales channels through virtual sales agents and more. But you need to keep digging deep to find these opportunities and ways to engage employees in the lasting, positive change that AI represents.
“It’s critical to uncover powerful top-down goals like these and identify how generation AI will transform the business in order to effect real, lasting change from the top,” says Kropp. “It is therefore very important that organizations actively experiment and invest in application development. But the most important work of the next three to five years will be addressing employee concerns and ensuring their engagement remains at the heart of your generative AI efforts.
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