Knowledge Center: Publication
Finding the right AI talent for your organization6/19/2018 Ryan Bulkoski and Sam Burman
Organizations looking to attract artificial intelligence (AI) talent are finding expertise scarce and the competition fierce. Beyond the big tech companies—often referred to as the FANG and BAT companies1—AI leadership is quickly becoming a necessary investment regardless of industry. Indeed, a recent study identified 400 discrete use cases for AI and analytics.2
Companies are taking notice. In a recent survey, 61% of executives said their organization plans to hire a chief AI officer in the next 24 months.3 Moreover, early adopters are cropping up in areas not traditionally associated with technology. In 2015, for example, Westfield Corporation—one of the world’s largest shopping center owners and managers—hired a chief data and analytics officer to guide its investments in advanced technology strategy. (For our interview with Westfield’s Raghav Lal, see “Podcast episode 5: In pursuit of omnichannel nirvana.”) Similarly, global insurer Aviva hired a chief digital officer who helped launch the Digital Garage—a lab that harnesses advanced analytics and AI to create new digital insurance products tailored to customers.4 In addition, the company plans to invest in and acquire fintech companies to close the competitive gap in insurance. Chief executive Mark Wilson’s statement that, for Aviva, data scientists are in higher demand than actuaries is a telling sign of the changing times.
Even with pervasive interest in AI, many companies are still perplexed about where to begin. Organizations know investing in the right person or team is crucial but have yet to build a cohesive strategy to support their AI goals. This interest has created a high demand for talent: in May 2018, LinkedIn listed more than 8,300 jobs in the United States alone that included the keywords “artificial intelligence.” Many of these positions are accompanied by six-figure salaries.5 Further, companies trying to fill AI roles are in stiff competition with technology firms that can shell out top dollar for talent. Even newly minted college graduates with advanced degrees in AI can, in extreme circumstances, command $300,000 a year, so leaders must evaluate whether they can afford top talent or need to build from the bottom up. Organizations must also determine the appropriate structure for an AI capability, which can be a challenge.
So how can companies located outside of AI hotbeds, and in industries other than tech, overcome these disadvantages to attract the right people? We recommend three tactics to help companies find, acquire, and retain AI talent that fits their organization. First, develop a clear AI strategy that reflects how AI can support the business. Second, evaluate organizational maturity to determine the company’s ability to benefit from AI talent. And third, formulate an AI talent profile to ensure that promising candidates can be successfully integrated into the organization and retained. Executing these tactics effectively can help companies lay the foundation for a sustainable AI effort.
1. Develop a clear—and well-supported—strategy
Given the plethora of ways in which AI could be deployed to further a company’s objectives, executive leadership teams must evaluate their business needs—both immediate and in the future—and clearly define how AI can help support them. One way to narrow the focus initially is to identify a discrete need—for example, natural language processing in customer experience or robotic process automation6 in supply chain management—and then bring in AI experts to conduct a pilot project to achieve quick wins. The results from these efforts can be used to enlighten business leaders on the applications and impact of AI in order to support enterprise-wide investments.
A top-three wealth management firm took this approach, hiring a head of AI to help the company get more from its institutional knowledge. The value proposition was clear: by finding a machine learning solution to help the company aggregate and analyze unstructured data (such as conversations among its experts), its financial advisers could provide better service to investors. In another example, a global pharmaceutical leader brought in an AI executive to enhance the company’s supply chain through the use of advanced analytics. In both cases, a general vision was outlined by the company, and the team homed in on a few specific use cases to tackle in the short term. Ultimately, both executives quickly built momentum, rapidly scaled their respective solutions across their organizations, and developed long-term strategies for investing in AI-driven approaches.
2. Evaluate your organization’s AI maturity
Executives responsible for hiring AI talent must assess their organization’s technology capabilities and gain the support of the C-suite for additional AI investments. On the former, organizations lacking the requisite foundation to support AI must build it before pursuing top talent. The reality is that many companies, especially those outside tech industries, are still at the beginning of their journey. For this reason, using pilot programs can be effective, as it helps companies build skills and learn as they go.
On the latter, failing to have proper buy-in and syndication can stop an otherwise promising AI program in its tracks. Strong executive leadership helps promote AI adoption and deployment.7 Cross-functional collaboration is also critical, given the need to tightly integrate most AI projects with the business. Without buy-in and meaningful coordination among functional leaders such as the CIO, CMO, and CFO, a fledgling AI executive might otherwise become frustrated and exit quickly, wasting valuable time, resources, and even goodwill. AI projects that fizzle without producing results will just make it harder to gain support for future efforts.
The endorsement of the C-suite should be reflected in the organizational positioning of the AI leader. Having an AI leader who reports to or works alongside the C-suite sends a clear message to the organization about the importance of AI.8 (See sidebar, “Organizational implications for AI executives.”)
A global mining company in the early stages of its AI journey, for example, hired an executive who could apply AI across the entirety of its value chain. Prior to making this bold decision, the board member responsible for technology, innovation, and sustainability explored the potential application of AI within the organization by visiting start-up incubators, academic communities, and technology events and seeking counsel from noncompeting industry leaders. Upon clearly defining the opportunity, the board developed a role to pursue it. The organization’s approach has been to build a center of excellence for all things data, machine learning, and AI. This function is small and agile while tapping start-up and academic communities to streamline innovation and execution.
The AI effort has generated operational benefits, including where to mine and how to mine, as well as informing commercial decision making on when to stockpile commodities versus when to sell (through macro- and microeconomic trend analysis) and how to lower the company’s environmental impact. In addition, AI-enabled predictive maintenance helped the company to better manage its heavy, capital-intensive machinery. All of these applications demonstrate how AI and data analytics were used to fundamentally reengineer the organization, as well as helping to make the company more environmentally responsible. These results were possible because the AI executive reports directly to the board. Without this critical support network, the role likely wouldn’t have come to fruition.
3. Formulate an AI talent profile
To determine the right cultural fit, companies must create a profile of the ideal candidate based on a combination of organizational maturity and strategy, including the right ratio of AI knowledge to executive experience. In many cases, this hire will have to acclimate quickly to a new environment, engender confidence among the C-suite, serve as an evangelist for AI, and work closely with leaders of functional areas or business units. Rising AI stars in tech companies often bring the backing of a prestigious brand name. Yet a strong pedigree is no guarantee that the executive possesses the leadership skills and emotional intelligence required to excel as a newly anointed “AI savior” in a more traditional organization. In many cases, a formal mentorship program can ease the individual’s onboarding process and help ensure his or her long-term loyalty.
An effective AI talent effort should consider not just compensation but also cultural fit. Striking this balance is critical to set both the AI hire and the company up for long-term success. On compensation, companies must be prepared to weather the “sticker shock” and in many cases pay above market rate in order to compete for talent. Companies do have levers to pull beyond compensation alone, however. Often, the opportunity to transform a company or an entire industry through AI can be a compelling challenge in its own right. If a company has an attractive mission—such as a social purpose or a focus on environmental sustainability—this could provide a counterweight to the generous equity packages of most tech giants. Over the past couple years, we have witnessed a significant increase in the desire of top talent to have a social-purpose angle in their next role or employer. This trait is especially true among younger executives. Other intangibles, such as the opportunity to form strategic partnerships with universities, publish company-sponsored research, or support important research projects can also make the opportunity more attractive.
One large transportation and logistics company, for example, focused its search on candidates who had previous experience navigating the complexities of a large enterprise. The company hired an executive to lead its AI effort and made plans to expand to an AI organization of more than 200 people with expertise in analytics, data science, and digital automation. The company’s success in selecting the initial hire—as well as that executive’s skill in attracting a roster of talented individuals—has enabled the company to build an AI ecosystem to support its business objectives.
Finding talented, experienced executives to head up an AI program is a different kind of challenge than filling traditional C-suite positions. The relatively recent emphasis on AI across industries has increased competition for qualified candidates. What’s more, the size of the investment required to hire an AI executive has raised the stakes. Since AI’s business uses are likely to rise in the coming years, companies should ensure that their journey starts soon—and with talent aligned to their strategy and operational capabilities.
Sidebar: Organizational implications for AI executives
To avoid overemphasizing a candidate’s academic pedigree and tech know-how, companies should consider the organizational implications as well as the skills the hire will need to excel in a new environment. A detailed candidate profile can help companies map the organizational implications of a hire along three vectors:
Who will the AI executive report to? A direct line to the CEO signals that AI is a top strategic priority. Reporting to the COO could indicate investments in AI are more executional. And if the AI executive is set to report to the CIO or CTO, AI might be perceived purely as a technology experiment rather than a more sweeping change. While none of these choices is right or wrong, each comes with its own implications as potential candidates evaluate an organization’s intention in hiring a senior AI executive.
Who are the AI leader’s peers? When the C-suite is designated as the AI executive’s key constituents, AI will naturally inform decision making. The leader will be free to influence and collaborate with his or her peers in technology, marketing, finance, supply chain, and other areas. However, if the AI executive is hired to lead a center of excellence, or as part of an R&D function, he or she will be responding to requests from business managers or viewed as an experimental investment that may or may not yield tangible results.
Who will this person lead in the organization? Companies have the choice to give an AI executive the authority to hire a brand-new team, or the AI effort may absorb some existing internal employees who have historically aligned with data and analytics categories (such as business intelligence or customer analytics). Oftentimes, the right answer is a blend of new and existing resources. While the initial investment in an AI executive may be costly, an even greater investment is required in building an AI team. Most AI executives are well connected and would prefer to make a number of quick hires directly from prior teams or from their network.
About the authors
Ryan Bulkoski (firstname.lastname@example.org) is a partner in Heidrick & Struggles’ San Francisco office; he leads the firm’s Artificial Intelligence Specialty Practice and is a member of the Digital Practice and the Disruptive Innovators Team.
Sam Burman (email@example.com) is a principal in the London office; he leads the Digital Practice in Europe and Africa and is a member of the Artificial Intelligence Specialty Practice and Disruptive Innovators Team.
1 FANG—Facebook, Amazon, Netflix, Google; BAT—Baidu, Alibaba, Tencent.
2 Michael Chui, James Manyika, Mehdi Miremadi, Nicolaus Henke, Rita Chung, Pieter Nel, and Sankalp Malhotra, “Notes from the AI frontier: Applications and value of deep learning,” McKinsey Global Institute, April 2018.
3 Teradata, State of Artificial Intelligence for Enterprises, 2017.
4 Oliver Ralph, “Aviva opens ‘digital garage’ in technology push,” Financial Times, January 18, 2016.
5 CB Insights, Top AI Trends to Watch in 2018, February 14, 2018.
6 Robotic process automation (RPA) is used to complete high-volume, routine operational tasks previously handled by humans.
7 Jacques Bughin, Eric Hazan, Sree Ramaswamy, Michael Chui, Tera Allas, Peter Dahlström, Nicolaus Henke, and Monica Trench, “How artificial intelligence can deliver real value to companies,” McKinsey Global Institute, June 2017.
8 Edward Qualtrough, “Aviva International CIO Fin Goulding interview—Bringing agile flow to ‘Jurassic’ insurance sector,” CIO, January 18, 2018.