Many organizations today think hiring a Chief AI Officer role (or similar) is enough to get ahead of the GenAI curve. While these leaders can help define the AI strategy for the organization, they might not be right for every business. Who you need at the AI helm largely depends on what you want to achieve.
For some organizations, hiring someone in a big AI role might be the best approach. But in this Leadership Labs Insight, Fawad Bajwa, Russell Reynolds’ Global AI Practice Leader, argues it’s worth assessing the different types of people needed for your AI strategy, as well as your organization’s ambition in this space.
Read on to learn how to drive a connected and cohesive approach to AI that goes beyond a ‘one-and-done’ recruitment drive.
Developing a successful AI strategy is an issue that hasn’t gone unnoticed in boardrooms. CEOs are being asked about their approach, covering business model assessments, productivity improvements, and radical product innovation, as new technologies are being rolled out to just about every function in the business.
Some are looking to the Chief Information Officer (CIO) for a tech solution, while others are turning to their Chief Data Officer for answers. And while leadership teams grapple with an enterprise-level strategy that connects the dots, the easy answer might just be: hire a Chief AI Officer.
But when it comes to AI strategy, does it require a dedicated C-suite role?
The answer, of course, is that it depends.
But the answer to capturing your AI opportunities and circumnavigating challenges might not be to just hire one, dedicated, person.
Applying AI is no longer just a tech opportunity. It’s a business transformation and radical product innovation opportunity. Here’s how to treat it as such.
So, if you’re looking for an AI leader that suits your organization’s ambitions, there are different roles you can consider beyond a straightforward Chief AI Officer. Here are three that can form part of a multi-faceted team to drive your goals forward.
1. AI Transformation leader
If an enterprise-wide view is essential to meet your wide-reaching AI strategy goals, you need someone on your team who has an enterprise-wide mandate. This person might be a broader transformation leader who isn’t necessarily deep in AI—but they do have to know the business really well, have experience in leading, and be trusted within the organization. They can also hire AI leaders supporting them to make the transformation happen, working across the various functions.
2. AI Product leader
If you want radical product innovation using AI, you need someone with a strong product background to get into the weeds of how AI can connect to your offering. This person will connect the voice of the customer to the technical realities of what is possible, and help bring new innovation to market, making the best of emerging technologies.
3. AI Innovation leader
If you’re looking for someone to push the organization’s thinking in terms of the art of the possible, you need someone at the very top who understands the business, as well as the possibilities AI can accomplish to elevate your entire organization. This could be one or two people, and they might already exist internally—it might even be your CEO.
But they need a nuanced understanding of the practical possibilities of AI and what it can achieve for your company, so sometimes it’s better to fill that role from someone on the ground. This could be a business leader or, if it’s the right fit for your organization, this is where a Chief AI Officer comes in.
Whether you pick and choose from these roles or decide you need all three, the benefit of the three-pronged approach is a team of deep technologists and data scientists, paired with leaders who know your business really well.
Now I’ve made my case against a sole C-suite level dedicated AI hire, I’m going to do a 180 and tell you when you actually should hire one.
If you are an ambitious company and looking to make a market shift and/or take a holistic view of your assets, then you do need a senior AI expert who is going to help you piece all this together.
A Chief AI Officer in the C-suite is a strategic systems thinker with an enterprise view. Someone who understands the nuances of the business, the voice of the customer, a sense of each of the functions, and what it would take to bring new, AI-enabled products to market. They’ll help define your AI strategy, all while keeping potential legal and ethical issues in mind.
It could also be a good fit if you want an anchor hire to send a signal about the direction of your business. It can help attract strong AI talent to the company and show you’re serious about this growing technology.
With that said, we expect this to be a change management role. Once everyone is using AI seamlessly, just like we have with mobile technology or the internet, we won’t need people to help figure out how to use it.
Today, we need leaders who can manage transformation, and those who understand the technology like the back of their hand.
The key to deciding whether a C-suite AI role is right for your business is defining the ambition of your business. Is AI changing the face of your products and services, or simply improving CX?
You also want to think about whether your tech infrastructure and data is in the right place to be undertaking a company-wide AI strategy—because you may need to do a more holistic, multi-prong transformation to capitalize on the available and fast improving technologies.
To that end, you might find that first you need a Chief Data Officer, before advancing to the world of AI.
That’s not to say that a Chief AI Officer is a redundant role: for the right company, they can form part of a leadership team driving change with deep expertise. They can help impact the bottom line, move into new markets, and transform industries with the strategic use of technologies.
But they’re also not a silver bullet. Before you jump to the big title, it pays to think about getting the right team in place to pull off such a large transformation.
Fawad Bajwa leads Russell Reynolds Associates’ AI, Analytics & Data Practice globally. He is based in New York and Toronto.