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Chief Artificial Intelligence Officer

Position Summary

The Chief Artificial Intelligence Officer (CAIO) is responsible for establishing and leading the organization’s enterprise-wide artificial intelligence strategy. This executive identifies opportunities to use AI to improve products, customer experiences, operational efficiency, decision-making, and long-term business performance.

The CAIO provides strategic direction for the responsible development, implementation, and governance of AI capabilities across the organization. This position partners with executive leadership and business, technology, data, legal, security, and Human Resources teams to ensure AI investments are aligned with organizational priorities, deliver measurable value, and are implemented securely, ethically, and responsibly.

Essential Duties and Responsibilities

AI Strategy and Leadership

• Develop and maintain an enterprise-wide AI strategy aligned with the organization’s business objectives, technology roadmap, and long-term growth priorities.
• Advise executive leadership on emerging AI capabilities, market developments, competitive risks, and investment opportunities.
• Identify and prioritize AI initiatives based on expected business value, feasibility, organizational readiness, risk, and resource requirements.
• Establish a scalable roadmap for progressing AI initiatives from concept and pilot stages through production implementation and enterprise adoption.
• Serve as the executive sponsor and primary organizational authority for AI strategy, governance, and responsible adoption.

Business and Product Innovation

• Partner with business and product leaders to identify opportunities to use AI to improve products, services, customer experiences, employee productivity, and operating performance.
• Evaluate opportunities for AI-enabled products, features, services, and business models that support revenue growth and competitive differentiation.
• Oversee the development and validation of AI proofs of concept, prototypes, and pilot programs.
• Ensure AI initiatives address clearly defined business problems and include measurable success criteria.
• Establish processes for evaluating, prioritizing, funding, and scaling AI investments.

AI Development and Implementation

• Provide executive oversight for the design, development, integration, deployment, and ongoing management of AI solutions.
• Partner with technology, engineering, data, and security leaders to establish the infrastructure, architecture, data capabilities, and operating practices required to support AI.
• Promote appropriate standards for model performance, reliability, explainability, monitoring, documentation, and lifecycle management.
• Ensure AI solutions are designed for scalability, maintainability, security, and integration with existing systems and business processes.
• Evaluate external AI platforms, models, vendors, and strategic partnerships when internal development is not the most effective approach.

Governance, Risk, and Responsible AI

• Establish and oversee an enterprise AI governance framework addressing responsible use, data privacy, cybersecurity, intellectual property, regulatory compliance, transparency, human oversight, and accountability.
• Define policies and standards governing the selection, development, testing, approval, deployment, monitoring, and retirement of AI solutions.
• Partner with Legal, Compliance, Information Security, Human Resources, and other stakeholders to identify and mitigate risks associated with AI use.
• Establish appropriate review and approval processes for high-impact or high-risk AI applications.
• Monitor the regulatory and legal environment affecting AI and recommend changes to organizational policies and practices.
• Promote responsible AI principles, including fairness, transparency, security, reliability, privacy, and appropriate human oversight.

Organizational Adoption and Change Management

• Lead organizational efforts to build AI awareness, readiness, and responsible adoption.
• Partner with Human Resources and business leaders to assess how AI may affect roles, skills, workforce planning, and organizational design.
• Develop education, training, and communication strategies that enable employees to use approved AI tools effectively and responsibly.
• Address adoption barriers and promote collaboration across business and technical teams.
• Establish communities of practice, innovation forums, or similar programs to share knowledge and encourage responsible experimentation.

Data and Technology Enablement

• Partner with technology and data leaders to improve data accessibility, quality, governance, security, and architecture in support of AI initiatives.
• Help establish enterprise standards for AI platforms, models, tools, integrations, and development practices.
• Ensure AI technology decisions are aligned with the broader enterprise architecture and cybersecurity strategy.
• Assess the organization’s AI maturity and recommend investments needed to strengthen its capabilities.

Performance Measurement

• Establish key performance indicators and reporting practices for measuring the operational, financial, customer, and strategic impact of AI initiatives.
• Monitor the performance, adoption, risks, and return on investment of the organization’s AI portfolio.
• Provide regular updates to executive leadership and other governing bodies regarding AI initiatives, investments, risks, and results.
• Reallocate resources or discontinue initiatives that do not demonstrate sufficient value, scalability, or strategic alignment.

Team and Partnership Leadership

• Build, lead, and develop internal AI capabilities, which may include AI engineering, machine learning, data science, automation, product management, governance, or related functions.
• Define the appropriate operating model for centralized and decentralized AI responsibilities.
• Recruit, develop, and retain talent with the technical, business, and governance capabilities required to support the AI strategy.
• Establish strategic relationships with technology providers, consultants, universities, research organizations, and other external partners.
• Perform other duties and responsibilities as assigned.

Required Qualifications

• Bachelor’s degree in computer science, artificial intelligence, data science, engineering, information systems, business, or a related field.
• Ten or more years of progressively responsible experience in technology, data, digital transformation, product development, business strategy, or a related field.
• Five or more years of senior leadership experience, including responsibility for enterprise-level initiatives, teams, budgets, or strategic programs.
• Demonstrated experience developing or implementing artificial intelligence, machine learning, generative AI, automation, or advanced analytics solutions.
• Experience translating emerging technology capabilities into practical business strategies and measurable organizational outcomes.
• Strong understanding of AI governance, data privacy, cybersecurity, intellectual property, regulatory risk, and responsible AI practices.
• Experience leading complex, cross-functional initiatives involving both business and technical stakeholders.

Preferred Qualifications

• Master’s degree in artificial intelligence, computer science, data science, engineering, business administration, or a related discipline.
• Executive-level experience in a technology, software, data, or digitally enabled organization.
• Experience launching AI-enabled products or scaling AI solutions within an enterprise environment.
• Experience developing AI governance policies, review processes, and risk-management frameworks.
• Familiarity with large language models, machine learning platforms, cloud architecture, data platforms, model lifecycle management, and AI security practices.

Knowledge, Skills, and Abilities

• Strong strategic thinking and the ability to connect technological capabilities with business priorities.
• Executive-level communication, presentation, and influencing skills.
• Ability to explain complex AI concepts, benefits, limitations, and risks to nontechnical audiences.
• Strong business and financial judgment, including experience evaluating investments and return on investment.
• Ability to lead organizational change and build alignment across diverse stakeholders.
• Strong understanding of AI technologies, industry trends, and implementation considerations.
• Sound judgment when balancing innovation, speed, cost, security, compliance, and organizational risk.
• Ability to develop effective teams and foster collaboration between business and technical functions.
• High degree of integrity, discretion, accountability, and ethical judgment.

Leadership Expectations

The Chief Artificial Intelligence Officer is expected to approach AI as an enterprise business capability rather than solely as a technology function. Success in this position requires balancing innovation with disciplined execution, responsible governance, organizational readiness, and measurable business value.

Language Ability:

Ability to read, analyze, and interpret trade publications, technical documentation, reports, and other documents. Ability to respond to common inquiries from customers, peers, or members of the business community. Ability to write communications and documentations grammatically correct for routine business correspondence. Ability to present to large groups short recaps of the past month’s events.

Reasoning Ability:

Ability to define problems, collect data, establish facts, and draw valid conclusions. Ability to interpret an extensive variety of technical instructions with abstract and concrete variables. Ability to determine whether unique scenarios are truly “one offs” or if they should be built into the list of items to review each time. Ability to think through how certain scenarios could be programmed, coded, or explain what repeatable scenarios need to be accounted for or should have alerts.

Computer Skills:

To perform this job successfully, an individual should have knowledge of Word Processing software; Spreadsheet software; Adobe PDF; Outlook.  Beneficial to have an understanding of some level of programming (such as Visual Basic).

Certificates and Licenses:

None listed

Supervisory Responsibilities:

Will supervise employees and be responsible for overall direction, coordination, and evaluation of the department. 

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.

The noise level in the work environment is usually quiet.

Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The employee must frequently lift and/or move up to 5 pounds and occasionally lift and/or move up to10 pounds. Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception and ability to adjust focus.

While performing the duties of this job, the employee is frequently required to stand; walk; sit and talk or hear. The employee is occasionally required to reach with hands and arms.

This job description describes the general nature and level of work expected for the position. It is not intended to represent an exhaustive list of all responsibilities, qualifications, or working conditions associated with the role.