Integrating AI Into Your Business and the Leadership Talent You Need to Make it Happen

Certain roles are critical for businesses investing in artificial intelligence. Leaders like the chief data officer and VP of AI product management can make all the difference in driving adoption and integration. Mike Doonan and Natalie Ryan of SPMB talk about recruiting for such talent, and how these leaders can help to deliver success.

April 21, 2023 – As companies across all sectors become aware that the use of AI can drive meaningful efficiencies and create a significant business impact, SPMB Executive Search’s Mike Doonan and Natalie Ryan have helped guide their clients integrating AI into their digital transformation efforts and overall business by placing leaders to drive this adoption and integration. The stakes are high and AI adoption has become a determining factor in the future success and relevancy of some of the world’s largest, most established brands and organizations. 

The role of chief data officer or chief analytics officer is vital for businesses investing in AI, according to Mr. Doonan. “This type of executive ensures the company makes the most out of its AI investments in terms of profitability, efficiency, and value-add,” he said. “Part of this work includes implementing AI governance (rules, processes, best practices) mechanisms across the business from a social, legal, ethical, and technical perspective. Depending on the specific business needs and nuances of an organization, a chief data officer can own data engineering (the tech platform) and data analytics (the math) or they can be under separate leaders. Regardless of where these data functions sit, the leader/s must get these groups working closely together since the data engineers are responsible for creating the architecture and ultimate scalability that supports the needs of the data scientists and business analysts. The ultimate outcome is that both functions work in harmony to produce proprietary data that is used in AI and machine learning-driven efforts that drive critical product, risk and broader business decisions.”

The top chief data officers I know are business executives before they are data people, says Mr. Doonan. They work closely with less technical business stakeholders, constantly seeking out new and inventive ways to solve big, meaty business problems in a scalable way. “These leaders need to be technical enough to be dangerous and garner the respect of the tech organization, so I prefer candidates who either have an engineering upbringing, or those who have advanced degrees in mathematics or science and worked their way up from data scientist roles into the analytics side of management,” he said. 

“A few years at a top tier consulting firm like McKinsey is also helpful, since folks coming from this background often have had to present and be credible in front of senior business leaders early in their career,” said Mr. Doonan. “However, I always warn against hiring someone senior directly out of consulting into their first operating role. For lower to mid level roles, hiring directly from consulting can be fine. However, a senior consulting executive’s first rodeo within an operating company can often be a bumpy ride. Let someone else teach them the implementation side of strategy, and then capitalize on that experience.”

Mike Doonan leads SPMB’s Digital Transformation and Data practices and has executed over 400 C-level and VP searches across all market verticals. He enables innovative pure-play technology companies such as Google/Cloud and Amazon/AWS to achieve scale by recruiting senior leaders that have been through large, complex growth scenarios. Mr. Doonan also works closely with large incumbents such as Disney, AT&T, Comcast, Capital One, and Under Armour to evolve their technology, IT, product, data, security, and digital capabilities.

“I strongly agree with Mike,” said Ms. Ryan. “The success of your AI and machine investments hinges on strategic planning for data acquisition, management, and governance. Without a solid data executive at the helm, achieving this is difficult.”

Setting the Vision

Another leadership role, which is underutilized and highly beneficial for companies aiming to optimize their AI adoption, is a VP of AI product management, according to Ms. Ryan. “An AI product leader is brought in to lead the productization of AI models — setting the vision and then delivering high-quality AI products for the business that drive financial impact and outstanding customer experience,” she said. “These leaders help to focus the data science team and create AI products with clear use cases, business value, and overall outcomes which is what companies expect when they invest in these types of initiatives.”

Since spearheading her first two head of machine learning product searches at the start of 2020, Ms. Ryan notes that more companies are investing in this type of leader so they can create better AI/ML products that drive tangible business outcomes.

Related: The Challenge of Finding Top AI Leaders

“Similar to a traditional product leader, an AI product leader is required to manage cross-functional diverse teams (product, design, data science, and engineering) to drive AI capabilities,” said Ms. Ryan. “This type of leader is  business-focused and customer-centric to lead the team to think beyond data analysis. The best executives in this role often come from highly technical backgrounds, typically with advanced education in quantitative fields. This is due to the complexity and ever-changing nature of AI products.”

Innovative Technology Environments

It is important to acknowledge that AI/ML product management is an emerging field, and as such, the talent pool is relatively small and inexperienced compared to other established functions, which may present some hiring challenges,” Ms. Ryan said. “However, the AI/ML product talent pool is in high demand — and these executives tend to be well compensated, so companies must be prepared to pay a premium to attract top talent.”

As a partner at SPMB, Natalie Ryan leads the firm’s Southern California team and places key executive leaders across North America with disruptive growth-stage technology companies, as well as tech giants seeking innovation at scale. She specializes in managing complex and high-stakes CEO and C-suite executive search projects.

Mr. Doonan has worked with big tech companies including Google and Amazon, as well as companies like Disney, AT&T, Capital One, Under Armour and Comcast who provide tech-enabled services and who are all bullish on AI investments. Some have found that using AI-driven insights to understand their customers and the state of their overall business has allowed them to create more targeted, deliberate customer experiences and aid in the success of their broader digital transformation journey. I can share that some of my clients are using AI-driven insights to redesign their IT infrastructure and manage their cloud spend, too,” Mr. Doonan said. “Further up the stack, the more information they have on customer behavior, transaction volumes, site/streaming traffic, etc. the more they can hone their infrastructure to scale and create more immersive, sticky customer experiences. It’s true that digital transformations can be lengthy, costly, and challenging. However, clients that are learning to harness AI investments are already seeing happier customers and business impact, which makes the journey well worth it.”

As Ms. Ryan shared earlier, the companies that have made the biggest advances in AI have had tons of data to play with over a long period of time – so target those companies to find the best candidates. “You’ll also need to do a deep assessment into your business needs, the data available, what shape it’s in, and business goals to find an appropriate candidate with the right skillset to tackle those problems,” Ms. Ryan said. “A candidate who’s only had perfect, clean data at say a digital first organization won’t necessarily have the chops to build out AI and machine learning capabilities within an  environment in more of a transformational state.”

Ms. Ryan also emphasizes that a thoughtful and candidate-driven interview process is crucial for in-demand data and AI leaders. She notes that given the  limited number of qualified individuals in the market, it’s important to take extra care when evaluating potential candidates. “To ensure a successful executive search, consider both engaging a reputable search firm with experience in this nuanced market like SPMB and making sure the hiring manager has a personal connection with top candidates,” said Ms. Ryan. 

Related: Attracting Top Talent in the Age of AI

Contributed by Scott A. Scanlon, Editor-in-Chief; Dale M. Zupsansky, Managing Editor; and Stephen Sawicki, Managing Editor – Hunt Scanlon Media

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