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Business leaders share 5 ways they're taking AI from pilot to use case

βœ‡Latest News
By: Jean Paik，Julia Hood
Workforce Innovation Series template with vertical, colorful stripes on the left and bottom sides. A blue-tinted photo of coworkers looking at computer monitors

Getty Images; Andrius Banelis for BI

In the business world, there are few areas that artificial intelligence hasn't touched. Many industries are rushing to adopt AI, and the technology is changing how employees collaborate and complete tasks.

Generative AI is a major buzzword for business leaders. But actually integrating AI can be a different story.

"A lot of our clients have dozens of AI pilots everywhere," Jack Azagury, the group chief executive for consulting at Accenture, said at one Workforce Innovation roundtable. "Very few have a coherent business case and a true reinvention and transformation."

How do companies move forward as the novelty of AI wears off? Business Insider's Julia Hood asked members of the Workforce Innovation board how they transitioned their AI pilots into real-world use cases. Board members shared five major ways their companies were moving AI from theory to operations.

"Before we go and tell our clients to embark on AI fully, we want to be an AI-first organization," said Anant Adya, an executive vice president, service-offering head, and head of Americas delivery at Infosys. "We want to show our clients we are using AI, whether it is in HR when it comes to driving better employee experience or when it comes to recruitment."

Members also highlighted employee training and peer-to-peer learning opportunities.

The roundtable participants were:

  • Anant Adya, an executive vice president, service-offering head, and head of Americas Delivery at Infosys.
  • Lucrecia Borgonovo, a chief talent and organizational-effectiveness officer at Mastercard.
  • Neil Murray, the CEO of Work Dynamics at JLL.
  • Justina Nixon-Saintil, a vice president and chief impact officer at IBM.
  • Marjorie Powell, a chief HR officer and senior vice president at AARP.

The following has been edited for length and clarity.

Identify early adopters, like human resources

Nixon-Saintil: Because we provide these platforms and solutions to clients, we are usually client zero. We implemented AI across our business and multiple functions, and one of the first things we did was our AskHR product, which I think answered over 94% of questions employees had.

HR employees now spend time doing higher-order work and partnerships with business units instead of answering basic questions that a virtual assistant can answer. I think that's when you start seeing a lot of the benefits of it.

Borgonovo: HR has been leading the way in terms of embedding AI to enhance the employee experience end to end, right before you hire somebody all the way to after they leave the organization. There are tons of opportunities to improve performance and productivity and provide greater personalization.

Invest in ongoing training

Adya: There are certain AI certifications and courses that everybody has to take to be knowledgeable about AI. So we are driving education in terms of what is the impact of AI, what is gen AI, what are LLMs, and how you look at use cases. And certainly educating everybody that it's not about job losses but about amplifying your potential to do more.

Powell: We have hands-on skill building. This past year we posted over 20 AI workshops helping teams integrate AI into their work. We really encourage our staff to participate. We have a product we're using behind our firewall, so they can engage and play with it. We're just telling them go ahead and try to break it, so they can give us feedback on what's working.

There was a team of people who said we want to see how you could use AI with PowerPoint or Excel. And they're finding, well, it's not so good in those things. But as it continues to grow, they'll be ready for that, and they'll know what it was able to do and what it wasn't. I think it's just making it fun, and that way it's not so scary.

Murray: Our internal large language model is now a widget on everybody's dashboard that is accessible on your landing page. Training is super important here to make people comfortable with it. Even if it's just an online module, you have to get people comfortable.

Nixon-Saintil: We've also done companywide upskilling. We had two Watsonx challenges. Watsonx is our AI data platform. This is one of the ways we've upskilled a majority of the organization. The outcome of that is there are some great ideas that employees actually ideated, and they're now implementing those ideas and solutions in different functions.

Borgonovo: Employees want to use AI, and I think they're eager to learn how to use AI to augment their jobs. For that, we built a three-tiered learning approach. One is democratizing access for everybody and building general knowledge of AI.

The second tier is much more role-specific. How do we drive new ways of working by having people in different roles embrace AI tools? Software engineering, consulting, sales β€” you name it. And then something we definitely want to build for the future is thinking proactively about how you re-skill people whose roles may be impacted by AI so they can become more comfortable doing high-level tasks or can shift to a different type of role that is emerging within the organization.

The other piece is where we're seeing the greatest demand internally, which is for knowledge management. It's gathering information from a lot of different sources in a very easy way.

Another job family that is very eager to get their hands on new AI technology is software engineering. We have taken a very measured approach in deploying coding assistants within the software-engineering community. This year we did a pilot with a subset of them using coding assistants. The idea is to just learn and, based on our learning, scale more broadly across our software-engineering community in 2025.

One of the really interesting learnings from this pilot was that the software engineers who were using the coding assistants probably the best were people who had received training. What we're learning is that before you start rolling out all of these technologies or AI-specific platforms for different job families, you have got to be really intentional about incorporating prompt training.

Unlock peer-to-peer learning

Powell: We have idea pitch competitions and a year-round idea pipeline program where people can put in ideas on how to use AI and share what they've learned. It sparks a lot of peer learning and creativity on our digital-first capabilities to help us with our digital transformation.

Then we collaborate through community. We have a generative-AI community of practice. This is somewhat like how companies have employee resource groups; we have communities of practice as well. They give employees a space to share their techniques and learn from each other and stay ahead of evolving trends. They meet monthly, they have an executive sponsor, and they have all kinds of activities and learning opportunities.

Murray: As we monitored AI use and what sort of questions were being asked, we identified super users across all departments β€” so the people who were capable of developing the most evolved prompts. I suppose those prompts are now appearing in pull-down menus to help people who maybe aren't as advanced in their use of it, because prompting is a really important part of this. And so the super users are driving everybody else to show them what's possible across the organization.

Find customer pain points to solve

Borgonovo: One of the use cases that drives not only knowledge management but also efficiencies is around customer support. Customer support is probably one of the areas that has been leading the way.

We have a customer onboarding process that can be very lengthy, very technical, involving hundreds of pages of documentation and reference materials. It was our first use case for a chat-based assistant that we processed in terms of streamlining and creating greater efficiency and a much better customer experience.

Reinforce responsible leadership

Powell: We want our leaders, people leaders particularly, to guide employees to use AI effectively and responsibly. We want to make sure they're emphasizing privacy, policy, and efficiency. So we encourage managers to point the staff toward training that we offer, and we offer quite a bit of training.

Read the original article on Business Insider

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