Does Your Organization Need a Dedicated AI Leader?

A recent PwC survey found that 73% of US companies have already adopted AI in at least some areas of their business. Meanwhile, one year after ChatGPT hit the market, more than half of the companies surveyed (54%) have implemented generative AI (GenAI in at least some areas of their business. 

With AI playing an increasingly important role in daily operations, the time may have arrived for businesses to appoint a dedicated AI leader, states Steven Hall, chief AI officer at technology research and advisory firm ISG, in an email interview. 

AI is changing business models across all sectors, Hall observes. "The market is moving extremely fast as internal teams accelerate adoption and also introduce risks," he notes. "The launch of GenAI democratized AI, similar to the launch of the iPhone, making every person in the business a 'citizen developer' or AI expert, without understanding the opportunities and risks." 

A dedicated leader can help an enterprise coordinate and prioritize AI efforts. This can include ensuring that the right data assets are used to train models, proper guardrails are established to manage risks, and prioritizing use cases and experiments without creating a bureaucracy that slows enterprise adoption, Hall says. 

All organizations designing, developing, or deploying AI systems should have a dedicated AI governance leader, adds Ashley Casovan, managing director of the International Association of Privacy Professionals' AI Governance Center, in an email interview. "Someone who will work to establish policies, processes, and other mechanisms to ensure that AI systems are built and deployed in a responsible and safe manner." 

Related:Can Generative AI and Data Quality Coexist?

Leader and Visionary 

AI leaders should be prepared to develop and promote enterprise AI strategy while creating a roadmap to drive the right priorities, says Diana Min, Accenture Federal Services’ data and AI strategy lead, via email. "This role requires constant cross-functional communication between executives and technical leads to establish and maintain organizational and technical governance." 

"Governance plays a critical role in ensuring a risk-mitigated implementation of AI at every scale of deployment," Min says. A strong AI leader is also needed to anchor all AI investments to strategic outcomes, she notes. "This requires a dedicated leader to work across all functions to drive a new operating model, [encourage] cross-collaboration, and maximize positive results and return on investments." 

Casovan says she's seeing a growing trend leading toward AI leaders who are responsible for both for AI technology and governance. 

Related:Data Leaders Say ‘AI Paralysis’ Stifling Adoption: Study

Hall believes that an AI leader is foremost a business leader and visionary. "The leader needs to understand the risk and concerns, but also the governance and frameworks to help the organization be successful," he explains. "The leader also needs to be realistic and inspiring, and must understand both the hype curve and potential." 

To allow AI to truly take root and become an effective value accelerator, the AI leader needs to report to and work with someone at the enterprise level who can finalize decisions on strategic changes, Min says. "Exploring, designing, developing, and optimizing AI capabilities requires strategic bold investments and continued governance to maximize ROI," she notes. "Therefore, maximizing proximity to someone with these characteristics is recommended." 

Qualifications 

A chief AI officer, or equivalent, is a coordinator, a facilitator, and a protector, says Shlomo Argamon, a professor and associate provost for AI at Touro University, in an email interview. "Someone with a technical background in computer science, statistics, or data science, who also has a track record of working with diverse teams, building collaborative relationships, and developing consensus around complex issues." He adds that since AI is fundamentally a human focused technology, the human factor is critical when selecting an AI leader. 

Related:Enabling Edge AI To Be Truly Transformative

AI leader qualifications vary, depending on where an organization is on its AI maturity journey. Currently, most organizations are in the experimental phase, Min says. "Therefore, an AI leader who's going to be most effective is someone who has a blend of high emotional quotient and what we at Accenture like to call technology quotient." She adds that an AI leader must also be comfortable working with C-suite and other business leaders to galvanize adoption and elevate AI fluency. 

Parting Thoughts 

With AI momentum rapidly increasing, virtually all enterprises can benefit by appointing an AI leader, even if the position isn't a full-time job, Hall says. "The technology is impacting every organization, and the risks and opportunities are too great to leave to chance." 

No single enterprise unit is able to effectively keep pace with AI developments, Argamon says. "It's essential for such work to be centralized and coordinated across the organization." He notes that like human resources, AI is a crosscutting function. "Also, like human resources, there are significant institutional risks that need to be managed expertly and in an integrated fashion."