The Twin Star of Accountability and Responsibility rules the lives of all CEOs and directors of public companies every day. But how do leaders move forward and own the outcome when everything around them changes?
Geopolitical and trade policies have changed in unprecedented ways in our lives, with technology evolving at a fierce pace and navigation becoming tricky and progressively elusive. All of these create new kinds of challenges in environments where partnerships, supply chains and vendor selection are even more important.
AI presents a special taste for these new challenges for decision makers: the confusion and opportunity that will surely strain resources and imagination. The pressure to select the right tools and agents, prioritize opportunities with strategies, manage risk effectively, and understand the movements of competitors, all adds to the burden on CEOs and boards to identify the right path for best results. What further complicates the path is the convergence of AI's other technologies (robots!) and inevitably immature technology policies, all imposing complex variables for security, privacy and effectiveness.
Obviously, there is no solution that fits every organization or every leader. However, most people can reach a productive AI adoption path by asking a few key questions, despite all the emergence and changing technology, government, trade and technology policies.
1. What are you trying to achieve with AI/generated AI? How does our technology support your business strategy?
a. Will our business use cases improve existing processes and capabilities, or will we introduce new features and workflows? What does it take to do with the latter?
2. Do you have the right resources to succeed with AI?
a. people: Do you have the right expertise to support relevant innovations, ask questions, discuss strategies, get and identify market information in a timely manner, and operate efficiently and responsibly with sophisticated tools?
b. data: Do I have the right to use the necessary internal and third party data? Are there any mature data governance practices, such as secure repositories, search, and communications infrastructure? Do you know the system and source of the data? Do you have the tools and training I need to manage data in my AI applications?
c. budget: Have you restructured your financial and time budgets into AI priorities?
d. Internal Stakeholders: Are the appropriate components in the table (including law, security, communication)?
e. External Partner: Do you have the right vendors and partners to support the AI ecosystem?
3. Are you growing procurement capabilities ready to do due diligence, or support AI tools and supply chains?
4. Have you updated metrics for success in AI use cases and tools? What is the traditional measure of success, or what will it look like in this emergency space and in the long run?
5. What do you need to respond to market changes? What is important?
6. What do customers expect? How do customers want to interact with us through technology and what do they need to know from us? What undermines trust?
7. How can we understand our key stakeholders and what decisions have been made so far? Did we allow them to assess the inevitable pivots needed in the future?
The challenges are ubiquitous, but the answers and journeys are inevitably individual to each organization, board of directors and leadership teams. These questions are the first steps to own roads from the wilderness and positive outcomes and celebrate the impact.
