When evaluating and using generative AI technologies as an executive, you should focus on the following key areas:

1. Business Goals: Begin with a clear understanding of what business goals you aim to achieve using generative AI. It could be generating automatic replies in customer service, creating marketing content, helping in product design, or other objectives. The objectives will be used to define “tasks” that are needed in helping to choose the right Generative AI.
2. Use Cases: Identify specific use cases in your business where generative AI can be applied. This could be based on a need to reduce manual effort or to better utilize data you already have. This is critical to the successful use of the technology.
3. Budget & Resources: Coordinate with your financial team to determine the budget for AI implementation – considering costs not only for software solutions but also for essential resources such as data scientists, hardware, data pre-processing tools, and ongoing maintenance.
4. Vendor Evaluation: Assess various AI technology providers based on their track record, client testimonials, ongoing support, cost, and how well their offerings align with your business needs.
5. ROI Analysis: Carry out a feasibility study to determine the return on investment. This could include expected time to see results, cost savings, efficiency improvement, revenue generation, and other key performance indicators.
6. Ethics and Regulations: Understand the ethical considerations and regulatory compliances related to AI. This includes understanding the data privacy laws, intellectual property rights, and potential biases in AI algorithms.
7. Proof of Concept: Consider running a small pilot project before a full-scale implementation to gauge the effectiveness of the technology and to make any necessary adjustments.
8. Up-skilling and Training: Investing in the training of your team to handle and manage AI solutions is pivotal. Understand the skills gap in your organization and plan accordingly.
9. Managing Change: Change management will play a key role in integrating AI into your business processes. Work internally to help employees understand the benefits of AI and alleviate any fears or anxieties.
10. Data Management: Superior quality and quantity of data are key for efficient functioning of AI systems. Data collection, cleaning, annotation, and management will be crucial.

The success of implementing AI at your organization will depend heavily on thoughtful planning, team collaboration, strong leadership, and a strategic vision that is centered around achieving business objectives. Remember, generative AI is a tool – it’s how you use it that will determine your success.

Strategically what should you do?

I would recommend focusing on these key areas as well:

1. Talent and Culture:

• Roles may be transformed or newly created due to Generative AI, impacting the talent landscape.
• Organizations are repurposing functions and adopting a “cost out, value in” philosophy to maximize impact.
• Up-skilling the workforce is crucial to meet the demands of an AI-driven future.

1. Leadership:

• Establish a tech-savvy leadership team capable of optimizing AI investments and commercializing AI capabilities and data assets.
• Cultivate a culture of innovation and transformation to embrace AI as a tool for enablement.

1. Organizational Structure:

• Review how Generative AI adoption impacts the current organizational structure.
• Evaluate whether AI and data teams should align with the technology function or business unit leaders.
• Reevaluate operating models and structures to accommodate automation and AI disruption.

1. Commercial Strategies:

• Integrate Generative AI into various tools and software to explore new avenues for product revenue generation.
• Utilize internal data and advanced algorithms to uncover valuable insights and identify trends.

1. Risk Management:

• Address ethical considerations, data privacy, and security concerns associated with Generative AI adoption.
• Establish robust internal policies, comply with global regulatory standards, and create a company culture infused with AI expertise.

By focusing on these areas—talent and culture, leadership, organizational structure, commercial strategies, and risk management—you can effectively lead your organization through the transformative potential of Generative AI technologies while ensuring ethical, sustainable, and successful outcomes.

References:

1. McKinsey & Company. (2024, February 21). What every CEO should know about generative AI. Retrieved from https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/what-every-ceo-should-know-about-generative-ai
2. Amazon Web Services. (2024, February 15). Generative AI/ML AWS Executive Insights. Retrieved from https://aws.amazon.com/campaigns/executive-leaders-uk-ie/generative-ai/
3. Voicebot.ai. (2023, August 17). Generative AI shifts CEO focus to productivity over customer experience [Chart]. Retrieved from https://voicebot.ai/2023/08/17/generative-ai-shifts-ceo-focus-to-productivity-over-customer-experience-chart/
4. Broadhurst Digital. (Year, Month Day). Top considerations for executives planning for generative AI. Retrieved from https://broadhurst.digital/blog/top-considerations-for-executives-planning-for-generative-ai
5. Russell Reynolds Associates. (Year, Month Day). Navigating the generative AI revolution. Retrieved from https://www.russellreynolds.com/en/insights/articles/navigating-the-generative-ai-revolution