Unleashing the Power of Female Leadership in Generative AI: "Corporate Readiness for GenAI: The Critical Role of IT"

As I continue the focus on AI as a game changer in the Enterprise space, we must speak to the role IT plays.  Our Topic #4, does just this..

As AI continues to reshape industries, Enterprise IT organizations play a central role in driving this transformation. IT is responsible for designing the solution, securing cross-functional alignment, and often... securing the necessary funding to support AI initiatives.

Regarding funding, many times IT must take point in articulating and demonstrating the Return on Investment (ROI), ensuring that the financial commitment to AI is not only justified but also clearly aligned with the broader business strategy. IT leaders must quantify and communicate how AI initiatives will drive tangible outcomes, from cost savings to enhanced customer experiences => Revenue $$ growth, ensuring continued executive and board-level support.

Overall, IT must prove AI’s strategic value, aligning various departments, and ensuring board-level approval for investment and ROI. Leaders within IT should treat these as critical actions, positioning IT as a strategic driver rather than merely a support function.

To be ready for this foundational shift, IT must:

• Prioritize internal customer value and align business objectives at the core of AI solutions.

• Emphasize that infrastructure, governance, and enablement are as critical to AI success as the overall vision.

To bring this vision to fruition, IT must guide the entire organization in leveraging AI’s transformative potential.  Every initiative should center around the customer, ensuring that AI deployments enhance value for both internal and external users. IT’s role involves ensuring that systems, tools, and infrastructure are optimized to boost customer experience, satisfaction, and measurable outcomes.

This encompasses equipping product teams with the right tools, providing sales teams with AI-driven insights, aligning partner teams with AI capabilities to address business needs, modernizing support services to meet evolving expectations, and delivering valuable customer experience insights to renewals teams via AI-powered data.

Let’s not kid ourselves, this is a HUGE lift. The journey begins by identifying where AI can deliver meaningful customer value and deliver efficiencies—both externally and internally across functions like finance, human resources, supply chain, and compliance.

Understanding pain points, inefficiencies, and data gaps is crucial for prioritizing AI's impact.

To reinforce the critical role of IT, Forbes (December 2024) states, "As the bridge between business innovation and technology expertise, CIOs must advocate, educate, and negotiate for all things related to AI".

Again, this is no small feat. As highlighted by Boston Consulting Group (BCG), only 22% of companies have advanced beyond the proof-of-concept (POC) stage with AI, and just 4% are generating substantial value from their AI initiatives.

Common factors limiting success include:

1. Technical Debt and Data Challenges: Many organizations face technical debt, complicating AI integration with existing systems. Moreover, accessing and managing quality data hinders AI scalability.

2. Lack of Clear Objectives and Integration: AI projects often lack well-defined goals or fail to integrate with broader business strategies, budgets, and operations, resulting in isolated efforts that don’t deliver measurable value.

3. Insufficient Investment in People and Processes: Successful AI implementation requires not just technology investment but also upskilling employees and refining business and IT processes to effectively leverage AI.  Note: Return on Investment (ROI) plays a critical role in this area, stay tuned for future articles regarding how to prepare!  

To avoid these pitfalls, CIOs and IT leaders must take a foundational role in operationalizing AI readiness across four key dimensions:

1. Data Infrastructure & Integrity:

   • Conduct a data maturity assessment: What data do we have, where is it stored, and is it AI-ready?

   • Modernize data pipelines and implement governance structures for ethical, secure, and compliant AI use.

2. AI Tooling & Experimentation Environments:

   • Provide safe sandboxes for testing AI use cases.

   • Curate and manage access to AI models (e.g., LLMs) that meet security, performance, and compliance standards.

3. Internal Enablement & Upskilling:

   • Collaborate with HR and business leaders to make role-specific AI fluency part of every team’s growth path (not just engineers).

   • Include foundational AI concepts (prompting, responsible use, risk awareness) in technical onboarding and internal learning platforms.

4. AI Governance & Collaboration Models:

   • Partner with legal, risk, and compliance leaders to establish AI governance frameworks, such as usage guidelines, vendor risk reviews, and audit protocols.

With these enablers in place and by partnering with cross-functional teams, IT can evolve from a back-end support function to an AI strategy accelerator—turning capability into transformation by aligning systems, talent, and governance to deliver secure, scalable value.

As highlighted in this Blog series, topics #2 and #3; The C-Suite's and Boards Role in Leading AI Transformation and Building Cross-Functional Teams for Successful GenAI Integration, these points are key to building a top-tier team and AI Council.  By partnering with IT leadership and creating new AI roles, organizations can achieve cross-functional alignment to ensure the strategic AI roadmap stays on course. While CIOs and IT leaders may initially face challenges in gaining the necessary authority, it’s essential for them to establish credibility with the C-suite and Board. This will ensure a unified, top-down AI strategy, avoiding siloed data sets and fragmented approaches.

As Gartner noted in their May 2024 survey, 'Sixty-seven percent of mature organizations are creating new roles for generative artificial intelligence (GenAI) and 87% of these organizations have a dedicated AI team.' This highlights the critical need for IT to drive these new roles in coordination, not in functional silos, ensuring that AI initiatives are integrated across the enterprise.

As you take these findings and stats in, key points are clear. CIOs and IT leaders are the critical bridge between business-centric innovation and technology know-how.  CIOs must advocate, educate and negotiate for all things AI and be the glue that ensure success of the enterprise AI strategy!

Sources:

1. Forbes, “CIOs: What Does It Mean to Be AI-Ready?” (December 17, 2024)

2. Boston Consulting Group (BCG), “Artificial Intelligence at Scale”, 2024.

3. Gartner Survey, May 2024, “AI Is Creating New Roles and Skills in Data & Analytics”.