The twin stars of accountability and responsibility rule every CEO and public company director’s life, day in and day out—to responsibly make decisions and be accountable for the results. But how do leaders move forward and own the outcomes when everything around them is changing?
Geopolitical and trade policies are shifting in ways unprecedented in our lifetimes, and technology is evolving at a blistering pace, making navigation tricky and progress elusive. All of this is creating new kinds of challenges in an environment where partnerships, supply chains and vendor selection are even more critical.
AI presents a particular flavor of these novel challenges for decision-makers—its disruptions and opportunities reliably strain resources—and the imagination. The pressure to select the right tools and agents, prioritize opportunities with strategy, effectively managing risk and understanding competitors’ moves, all heighten the burden on CEOs and boards to discern the right path for the best results. Further complicating the path is the convergence of AI with other technologies (robots!) and necessarily immature technology policies, all of which impose complex variables for security, privacy and efficacy.
Obviously, there is no solution fit for all organizations or all leaders. However, most can get onto a productive AI adoption path by asking some key questions, even as the technology, governments, trade and technology policies all are emerging and shifting.
1. What are we trying to accomplish with AI/generative AI? How does our technology support our business strategy?
a. Do our business use cases improve existing processes and functions or rather, introduce new capabilities and workflows? When and what would it take to do the latter?
2. Do we have the right resources in place to be successful with AI?
a. People: Do we have the right expertise around us to support relevant innovation, ask questions, discuss strategy, obtain and discern market information on a timely basis, and operate efficiently and responsibly with advanced tools?
b. Data: Do we have access and the rights to use the internal and third-party data that we need? Do we have mature data governance practices, including secure repositories, retrieval and communications infrastructure? Do we know our data’s lineage and provenance where we must? Do we have the tools and training we need to manage data for AI applications?
c. Budgets: Have we realigned financial and time budgets to AI priorities?
d. Internal stakeholders: Are the right constituents at the table (including legal, security and comms)?
e. External partners: Do we have the right vendors and partners to support an AI ecosystem?
3. Is our procurement function upskilled and ready to do due diligence, transact and support our AI tools and supply chain?
4. Have we updated our metrics for success to AI use cases and tools? Both traditional measures of success or what good looks like in this emergent space, and over the longer term?
5. What do we need to keep pace with the changes in the marketplace? What matters?
6. What do our customers expect? How do customers want to engage with us over technology, and what do they need to know from us? What undermines trust?
7. How can we engage key stakeholders so they understand our positions and the decisions that have been made to date? Have we enabled them to appreciate inevitable pivots that will be needed down the road?
While the challenges are ubiquitous, the answers and journey are necessarily individual to each organization, board and leadership team. These questions are the first steps on a path out of the wilderness and toward owning positive outcomes and celebrating impact.
