Your AI transformation depends on these 5 business tactics

Aiming for a successful AI transformation is great, but if you can’t lead the initiative effectively, you won’t deliver the results the business demands.

With experts suggesting increasing numbers of companies are turning their attention from digital to AI transformation, here are five ways to ensure your organization reaps the rewards from emerging technology.  

Also: 4 ways to turn generative AI experiments into real business value

1. Partner with your peers

Gabriela Vogel, senior director analyst in the Executive Leadership of Digital Business practice at research firm Gartner, said digital leaders must focus urgently on exploiting emerging technology effectively.

“CIOs who don’t understand the focus on value — and make promises about AI without thinking about what they are getting involved with — might not stay at the top. They will lose power, they will lose inference, and potentially even lose their jobs.”

Vogel told ZDNET that CIOs often lead AI initiatives, but other executives are interested.

“The CFO is taking this technology seriously and trying to understand, ‘How are we going to make money out of AI?'” she said.

“They’re spending a decent amount of time trying to understand this area, more than many other executives within the C-suite, and so they’re going to have an influence.”

Also: The secret to successful digital initiatives is pretty simple, according to Gartner

Vogel said CFOs don’t want to be the executives responsible for emerging technology, but they want to be known as the individuals who helped deliver its benefits.

“So, the CFO is a great person to partner with if you want to make that shift into the business,” she said. “I would say they’re the best partner you could have now.”

2. Create a working group

James Fleming, CIO at Francis Crick Institute, said the digital leader’s role in AI is to provide oversight within the IT department and across the business.

“There’s got to be a degree of leading from the front and making it OK for your team to think about these questions and become experts in them, and then you’ve got to guide the rest of the organization along that journey.”

Fleming told ZDNET his world-leading research institute established a working group to assess AI. This group includes representatives from across the organization, including science, operations, legal, and HR.

“We posed several questions to that group, ‘How should we use it? What restrictions should we put on it, if any? Is there a case for investment in any of this? Should we buy enterprise licenses for ChatGPT tomorrow, for example?'” he said.

Also: Technologist Bruce Schneier on security, society, and why we need ‘public AI’ models

Fleming said the group didn’t find a killer use case that justified a huge investment in generative AI (Gen AI).

Instead, the group saw smaller, point use cases for new best-practice processes.

“We continue to pose those questions to the group about potential applications as we go,” he said.

“So, for example, the Crick is hugely multinational, and many researchers are writing grant applications in English, which is not their first language. Writing fluently can be an incredible boon when trying to get your ideas across.”

3. Optimise your resources

Bruno Marie-Rose, chief information and technology officer of the Paris 2024 Organising Committee for the Olympic and Paralympic Games, said the key to leading AI transformations is turning new personal habits into business benefits.

“Maturity is crucial for the International Organizing Committee,” he said. “Having an approach where you can say, ‘I’m four years ahead of the Opening Ceremony and need to progress, what do you advise?'”

Marie-Rose told ZDNET that one area where AI can prove beneficial is using data to help optimize the use of resources across the Olympics.

Also: Generative AI doesn’t have to be a power hog after all

Proof-of-concept studies during the Games examined how emerging technology could be applied, including using data to optimize on-site resources.

“For the Media Center, do you need a 200-square-meter room permanently? Or will this room only be fully utilized for the finals of the 100 meters? If that’s true, how could we optimize the number of journalists and the space?” said Marie-Rose.

“So, it will be key for the future to optimize the resources that we provide as an Organizing Committee, with all the difficulties we face, and having insight from emerging technology to enable that flexibility is a crucial part of the approach.”

4. Reduce people’s fears

Ollie Wildeman, vice president of customer services at travel specialist Big Bus Tours, said executives who explore AI will discover three types of people are worried.

“It will be the people on the front line who think their jobs will be replaced, it will be the people who manage those guys, and stakeholders will worry about the money you’re putting in and what will happen to the customer satisfaction scores in the long run,” he said.

Wildeman told ZDNET how Big Bus Tours uses Freshworks’ Customer Service Suite omnichannel support software, including AI-powered chatbots and ticketing.

As the executive leading the implementation, he has proven that emerging technology can have a positive impact. Front-line staff have seen how AI makes their work easier.

“We’re using our agents for more things, more value,” said Wildeman. “Rather than using an agent to respond to a query that could be read on the website, we’re using them to make a sale or respond in a personalized manner to reviews. The agents can see there are more diverse things to do.”

Also: AI is making us smarter, says AI pioneer Terry Sejnowski

Managers, meanwhile, have seen a well-trained AI can be trusted to push high-quality answers to customers.

“The people managers I spoke to at first said, ‘Ah, yeah, but if you get an AI, it’s just going to push out the same canned response to every customer. It’s going to seem robotic.’ However, in reality, Gen AI varies the language, so you have a better customer-facing product.”

Wildeman said happy customers mean happy stakeholders. His organization ensures customers know they’re interacting with a bot to keep satisfaction levels on track.

“We always indicate that we’re using a generative system. We don’t pretend it’s an agent.”

5. Don’t poison the well

Jon Grainger, CTO at legal firm DWF, said successful AI transformations ensure the data that feeds IT systems is well-managed and trustworthy.

“You can’t do stuff without your data being right,” he said. “You can go much deeper — and be much more solid on your outcomes and what you’re trying to achieve — as your data gets better.”

Microsoft Copilot is available to DWF employees. The rollout process starts with Teams and proceeds to Office once checks are complete.

Grainger told ZDNET the technology is used to transcribe meetings and provide meeting recaps, which can be particularly useful if you return to a conversation after an event.

Also: 3 ways to build strong data foundations for AI implementation, according to business leaders

He said organizations can already do some cool stuff with Gen AI, even when data is unstructured — but AI leaders should create as much structure as possible.

“Generative AI might not necessarily know the difference between two identical documents,” he said. “If one document has poor content and the other one has good content, the basis of probability means it might select either of those documents for your results.”

Grainger said placing data quality at the heart of the firm’s business strategy has helped to bring structure to information management processes.

“We talk about not poisoning the well,” he said. “You want to have a very well-curated, contained set of content. Then you say to your Copilot, ‘Don’t look anywhere else apart from what’s in that well.’ And that approach is part of our strategy.”