Gartner: AI is disruptive enough to warrant a dedicated owner, but that person probably doesn’t need a C-suite title — at least not yet.
Don’t Rush to Appoint a Chief AI Officer
AI is disruptive enough to warrant a dedicated owner, but that person probably doesn’t need a C-suite title — at least not yet.While some enterprises may opt for a “chief AI officer,” a “head of AI” is enough for most to integrate AI into business strategy.
Big Picture
Focus on a value-driving business strategy infused with AI
Too often, organizations have an AI technology roadmap masquerading as a strategy. They fail to recognize that activities around AI and GenAI are business, economic, social, ethical and technology decisions.
Avoiding this mistake requires a holistic, integrated approach with clear leadership and governance. However, this does not mean that organizations should rush to appoint a chief AI officer. For most, a head of AI who is not at the C-suite level will be perfectly capable of managing the two key aspects of AI strategy execution: orchestration and multidisciplinary governance.
Who leads the charge on AI for business
- Many organizations are still debating where the responsibility for AI and GenAI initiatives lies. A recent Gartner survey found that a diverse set of leaders is currently accountable for AI delivery.
- Our research shows that the head of AI must combine business and technology leadership to effectively assess the possibilities, power and perils of AI and GenAI.
- Government agencies will see increasing mandates on AI oversight, including a recent U.S. directive that U.S. government agencies designate a chief AI officer to lead and govern activities.
3 critical success factors for AI initiatives
- Aligned business strategy: Focus on building a value story, which illustrates progress toward business outcomes, tied to an organization’s business strategy. The more you are willing to rethink and recalibrate your business, the greater the potential impact of AI.
- Collaborative orchestration: There will be many concurrent AI and GenAI initiatives that require functional, technical, security, D&A and many other organizational resources. For the best chance of success, orchestrate them together.
- Multidisciplinary governance: One-size-fits-all models are too restrictive, while siloed governance limits coordination and leads to inconsistent behavioral standards throughout the organization.
Take a synergistic, multidisciplinary and iterative approach
- Areas of strategy, orchestration and governance include:
- Strategic business goals and alignment
- Operation execution
- Measurement
- AI-ready data strategy and ongoing curation
- Security
- Governance
- Risk and regulatory
- Talent shifts and dexterity (inclusive of AI literacy and trust program)
- Trust level and behavioral shifts in decision making
- Ethics and compliance
- None of this is a one-time task. Multidisciplinary teams must iteratively revisit each item and dynamically adjust using a risk-adjusted, repeatable approach.
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