In a world filled with AI innovation, we caught up with Amy Challen, Global Head of AI at Shell, to hear about how the energy company has been embracing Generative AI.
Amy embarked on her journey into the realm of data and AI within the academic sphere. After dedicating a decade to academia with a PostDoc and PhD in data science, she transitioned into the role of a management consultant. Seizing the opportunity that followed, Amy played a key part in establishing McKinsey’s presence in the field of data science. Since joining Shell in 2019, Amy has assumed a pivotal role, leading data science teams and harmonizing AI and data strategies with business opportunities. Her expertise extends to bridging the knowledge gap associated with LLM models.
Working at Shell, Amy explains how the key since joining is connecting data science with business opportunities to drive value from AI.
Managing AI change with business leaders
At Shell, Amy explains that the company has been experimenting with LLMs for many years. “The potential of AI is huge and tends to be underleveraged in large corporate companies, she says.” However, she explains that despite the excitement, business leaders have several external risks to consider, such as cybersecurity and information leakage. One of the biggest risks amidst fast AI growth, however, is businesses that fail to deliver value when injecting resources into the AI.
Business and product teams, Amy explains, are important to delve into these AI-led strategies and ensure that they are effective.
To find success with AI, be really clear about the business goals; Amy says, “Prioritise what use cases you want to solve and create a product strategy around that,”. Secondly, remember what business you are at the core “We’re an energy company, so we need to focus on what we know we can do well and figure out how AI will help us reach those goals.” She adds, “Leverage existing partners — AI innovation can be such a huge task. don’t work alone, collaborate with others,”
Additionally, teams resistant to change may create friction in the process. Consequently, bringing everyone on the AI journey is imperative. Amy adds, “It’s crucial to be clear about business intentions, ensuring everyone is on the same page,” she highlights. Introducing new features in a large enterprise hinges on effective change management. Amy stresses the need to illuminate the opportunities a new product or feature may bring, justifying the change management efforts.
Upskilling with Generative AI at Shell
A key journey for Amy and her team to embark on in the coming year is to upskill the entire workforce. Shell has recognised the long-term effects that a skilled Generative AI team can bring. However, Amy recognises that a huge challenge lies ahead.
“Our change management program isn’t there yet. We have a lot of work to do to educate more people about Generative AI within the company,” Amy says, “However we want to ensure that the whole organisation knows what AI can add to their skill set. It’s a team sport at the end of the day.” Amy explains how, in 2023, her team launched a series of webcasts to promote understanding of generative AI, the risks, and how to use these technologies safely in Shell. “These were well received, but we need to reach a larger audience,” she adds.
Amy and her team have also run in-person training for data scientists and technologists, around AI ethics and compliance. “This will become increasingly important with the EU’s AI Act coming in. We will continue to run these sessions to ensure widespread understanding of the issues,” she says.
“So far, we have been training General Managers to use this to their advantage in their roles both practically and deal with the psychological impacts of change,” she adds, “we are also training IT managers in what to look out for with generative AI, both in terms of risks and opportunities,”
Amy believes that it’s imperative for organisations to have a workforce that is able to use AI. It will be a huge advantage for now and in the future to know how it works and the risks that it may bring.
Do product managers need to be technical?
Despite upskilling in AI, Amy still believes that generalists matter in the world of technical individuals. “I’m a huge believer in talented generalists,” she says. Product managers and business analysts are smart and driven. They learn quickly and communicate well. Critical thinking and soft skills are imperative to building AI tools and products.
Amy adds that product managers must understand enough about how different technologies work to problem-solve around blockers and make sensible decisions. “This is not because they need to come up with all the ideas – you’ll have technical people who are on point to do that – but you need to be able to judge whether the ideas are good enough, whether something’s missing, and what we should try as a way ahead,” she says.
In a world where every professional is becoming more specialised, generalists are even more imperative to add value to products. “Products are not just about the technical delivery – a big part is about whether the technical features are even what’s needed!” Amy emphasises, “Having someone whose role is not purely technical is critical to making the teamwork – they take a different perspective – present the customer’s side, if you like – and this leads to a better outcome.”
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