People will be the key to generative AI success

Change management and skills development are arguably the most crucial components of a fruitful generative AI strategy

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History teaches us many lessons. With the introduction of new technologies in the past, leaders enthusiastically invested without thinking enough about the impact on their people and how they would adapt. 

The advent of generative AI adoption offers an opportunity to avoid this pitfall and, instead, liberate and better leverage the talent that can be found in every organisation. To do so requires leaders to help employees prepare for a shift in the way they do their jobs, and ensure they have the skills needed to succeed. Equally, leaders play a critical role in helping employees understand how the technology will benefit them. With the right strategy in place, GenAI adoption can be a win-win situation for organisations and employees.

The thing that’s holding many organisations back is investment in change management

“The thing that’s holding many organisations back is investment in change management,” says Phil Le-Brun, director of enterprise strategy at AWS, adding that many technology transformations go awry when leaders fail to support staff through the transition. 

Belinda Finch, CIO and executive vice president at IFS, agrees, noting that when digital transformation was the primary focus a decade ago, many companies adopted a technology-first approach. “All of those programmes started to fail,” she says. “It was those later adopters who realised that it wasn’t just about the technology. The big thing was about changing the culture, changing the way that the organisation worked. AI is no different. You’ve got to have money in your budget for change management if you want to implement new technology.” 

Leaders should contemplate the bigger picture and consider three key areas to ensure a successful GenAI integration into the company. They must understand how employees might respond to change, invest in skills development, and determine clear objectives and ownership.

Anticipate how employees might respond to AI 

It is important to consider employees’ varying levels of enthusiasm and apprehension regarding new technology. Le-Brun notes that individual reactions often depend on the type of technology and their familiarity with it. 

“In one area I may be an early adopter,” he explains. “So just give me the freedom to learn and the ability to practice. In other areas, I may be a bit cynical and need to see how the technology will help achieve a business outcome. And in some cases, I may be fearful. I’ve felt this in my career many times. My skill sets are changing. What does that mean for my career path? Will I be given the opportunity to learn?” Leaders must be prepared to address these different attitudes towards technology to avoid alienating staff. 

Finch adds: “The people side of this is more complicated than the technology side. A lot of it is about getting people’s heads around the fact that AI doesn’t mean that they’re going to lose their jobs; it just means that they’re going to do their job differently and learn new skills.” 

Oscar Fernandez, director and head of asset management tech transformation and architecture at Swiss Re agrees that reassuring staff and demonstrating how AI can personally benefit them is crucial for gaining their support. He gives the example of the mundane tasks that can be taken on by AI. “Nobody enjoys those. So there’s a clear pro there with enhanced job satisfaction. This should also have an impact on productivity, as employees can then use the time for more rewarding and value-generating work.”

Clare Walsh, director of education at the Institute of Analytics, adds: “One of the challenges we have is that many of us carry with us the mental map of what happened with deindustrialisation, or offshoring, where whole factories closed down and industries vanished. We fear a repeat of that scenario, but it’s not the same. 

“When told that some of their data cleaning process can be automated, I’ve never heard anyone say, ‘Oh, I would love to do it myself’. When it comes down to practical examples, that’s not the way that conversation goes.” 

But Walsh believes a lack of clarity about how technology will be used and regulated is causing hesitation among leaders and employees alike. “All of these factors create feelings of uncertainty, perhaps unnecessarily. We must ensure we have the right professional skills in our offices to instil confidence and move forward,” she says. 

Reskill and upskill employees to capitalise on GenAI 

Fernandez emphasises the need to be agile when working with a new and constantly evolving technology. “If I rewind one year, we weren’t sure whether prompt engineering was just hype or a necessary skill. Now we know it’s important, so you have to learn how to use it to extract the value of this technology,” he says.

“It’s also a fundamentally different way to work with generative AI than with more deterministic models. So you need to understand how to adapt your skills and processes when it comes to things such as model validation, repeatability of results and building reliable solutions. That’s a whole different way of working with technology.”

You can’t innovate without learning and experimenting

Finch points out that, when adapting to GenAI, people need to understand they don’t necessarily need to be good at solving the problem themselves anymore. “What they need to be good at is describing the problem they need to fix because AI can handle the problem-solving aspect,” she says. “And that’s a massive skill and mindset shift. That’s something that we need to start teaching in schools. That’s the skillset we’re going to need in the future.” 

Le-Brun agrees, saying that organisations should always be training their people and a continuous learning environment is a massive selling point for current and future employees. “You can’t innovate without learning and experimenting,” he adds. 

Determine clear objectives and ownership 

Finch suggests a shift in perspective when deciding who should head up the business transformation. The responsibility shouldn’t automatically fall to the CIO simply because the change involves technology. Instead, she argues for a role closer to the business operations, such as the COO or the CFO, to lead the charge. “The organisation should be driving AI. It should not be the tech driving the organisation,” she says. 

Le-Brun agrees that organisations need to think carefully about who leads and how they will go about driving cultural change across the organisation: “What’s that role designed to achieve? It’s really about rewiring the organisation, it’s not about creating another organisational silo.” 

He also points out that ensuring every leader has exposure to GenAI will help. “If your CEO or CFO hasn’t done some prompts engineering, why not? It’s easy to access. Get them hands-on with the technology and you can have a conversation about its implications. And they start to learn through doing.” 

Ultimately people are going to be drivers of change. “We know that change does not happen at the pace of technological change,” says Walsh. “It happens when people are ready to adopt.”

Find out more about how AWS can help you on your GenAI journey