The Board’s AI Imperative: A Risk Management Checklist to Unlock Next-Gen Growth and Shareholder Value

By Zehra Cataltepe, CEO of TAZI.AI, and Menekse Gencer, CEO of WesPay Payments Association

The call to action for boards to understand and oversee artificial intelligence (AI) is clear. Whereas companies had previously set aside significant spans of time to transform their customer experiences, operations, products, and cost effectiveness, today many are adopting AI to revolutionize and transform business operations to achieve outcomes at a fraction of the time, costs, and resources. While the opportunities are vast, it’s necessary to effectively balance the competing demands of moving quickly while  managing risk and ensuring compliance. 

This article offers a checklist for board members to identify what “good” looks like with respect to AI  implementation. It  outlines key questions across four areas: data appropriateness, customer and proprietary data protection, model explainability (for highly regulated industries such as banks), and human capital readiness. Given subject matter experts may vary by the AI business use case, boards need to be able to identify the relevant experts, such as the Chief Information Officer (CIO), Chief Experience Officer (CXO), Chief Data and Analytics Officer (CDAO), Chief Financial Officer (CFO), Human Resources, and possibly others, to answer the following questions:

1. Data Appropriateness

• How does our company ensure data privacy and security in AI models?     
• What processes are in place to continuously monitor and update data relevance?
• What are the most important data elements for model performance and what is the business value at risk if they become unavailable?
• How do we identify, prevent, and mitigate potential biases in AI models?

2. Customer and Proprietary Data Protection

• What measures are in place to anonymize and protect sensitive data?
• How do we ensure strict access controls and encryption for AI-related data?
• What is our vendor due diligence process for third-party AI solutions?

3. Model Explainability and Compliance

• How do we ensure our AI models are interpretable and compliant with relevant regulations?
• What explainable artificial intelligence (XAI) techniques are we employing to enable human users to understand and trust the results and outputs of complex model decisions?
• Who are the recipients of the AI explanations and what actions do they take based on the explanations?
• How often do we review and validate our AI models, and who is involved in this process?
• How and how fast do we fix models and data when there is data or model drift?

4. Human Capital Readiness

• Has our company established and disseminated clear employee AI policies and training and what is our practice to update and monitor these?     
• Does our current incentive structure support optimizing areas that AI can help transform such as maximizing customer lifetime value (e.g. if our P&Ls are product-based)?     
• What new KPIs can we implement and measure to shift towards customer-centric objectives?
• How are we fostering collaboration between data, technical, business, and compliance teams?
• How are we creating a safe and compliant experimentation environment for our teams to try new ideas utilizing AI and safely test, fail or succeed?
• How do we continuously listen to our customer voice and make the necessary updates on our systems, to make sure that our solutions are serving our customers’ best interest?

By being a responsible steward, tackling the above questions, and evaluating AI risks through a standard risk management framework and an iterative and adaptive process, boards can guide their companies to responsibly harness AI’s transformative potential and unlock opportunities for growth and innovation. Moreover, as companies look ahead to realize the benefits of AI, it’s important to establish a culture that is open to cooperation and failing fast, compliance in the face of new and changing regulations, and a breakdown of AI responsibilities (similar to the four key areas noted above) so that individual employees are empowered to manage each part successfully.

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Zehra Cataltepe is the CEO of TAZI.AI, a patented adaptive, explainable AI and Generative AI platform, accoladed in more than 30 Gartner reports, including a Cool Vendor and Magic Quadrant CAIDS report. With the retention and fraud solutions built on the TAZI platform, Zehra aims to enable non-technical users to configure, control, cooperate with and also take responsibility for AI and GenAI systems. To date, tens of enterprises have created tens of millions of dollars of value utilizing this kind of adaptive and responsible AI. Zehra earned her M.S. and PhD in Computer Science from California Institute of Technology, has experience both in academia and industry which led to more than 100 AI papers and 14 issued patents. She is a Forbes Technology Council Member and frequently authors articles around AI there.  She was honored as “Woman Entrepreneur of the Year” in 2020 and 2019 by Women in AI in Europe, Microsoft Turkey, and Istanbul Chamber of Commerce.

Menekse Gencer is the incoming CEO of WesPay Payments Association and serves on the Board of Directors of FINRA Foundation and the Advisory Board of Darwinium cybersecurity firm. As SVP of Digital Sales and Onboarding at Wells Fargo, she successfully led digital transformation across nine business lines during the onset of regulatory action and crisis management for 12,000 contact center members during COVID. She was instrumental in launching emerging digital payments products as Head of Mobile Business Development at PayPal, as an advisor to The Federal Reserve Bank’s Faster Payments Initiative, and as the advisor to founder and CEO of bKash. Ms. Gencer was previously honored as “One of 31 Women Strengthening the Connection between Finance & Technology” globally by Silicon Republic and has been a frequent author and speaker around innovation and financial services at conferences globally. She earned an MBA from The Wharton School of Business in Strategic Management and a BA in Economics from Harvard University.