CEO decision-making in the age of AI
CEOs have generally built a vision of the world to come that’s positive and AI for good must be prioritized, to make that vision a reality. Use the action guide that follows to assess your own decision-making and how best to take it to the next level.
The rush to action is understandable. Three quarters of CEOs (75%) believe that the enterprise with the most advanced generative AI will win and they say competitive advantage depends upon it. As they race toward AI superiority, 43% of CEOs say their enterprises are already using generative AI to inform strategic decisions, 36% for operational decisions, and 50% are integrating it into their products and services.
Better decision for a better world
To be a passive consumer or a wise AI value creator. CEOs need to define a clear plan and charge ahead, have the right capabilities in place, and handle disruptions of all shapes and sizes without slowing down or losing focus on strategic vision. Leaders can’t be distracted by shiny objects, lured down dark alleys, tempted by easy fixes, or lulled into complacency.
Source Truth
Organization should have flow chart for their working process. It should have inclusive and exclusive conditional and non-conditional statements for their resource inputs. Decision making based on system feedbacks for process improvements. And at any point should be able to locate and control original source.
Decision making
Decision-making is not just taking data and trying to model accurately but spending time also on the uncertainties and working around those combination of data, human judgment, and people’s opinion. The best decisions are those where collaboration informs the process. So, we take input from diverse groups—subject matter experts, data analysts, business leaders, and frontline employees who interact with customers. We take input from all these categories before making a decision. Decision-making based on intuition, common sense, and knowledge is very good and should never be lost, stays well-positioned going forward. The more analytic support we have, the better. So try to engage your team before making an important decision.
Inputs for decision making
CEOs draw from a variety of inputs when making strategic decisions. An increase in the amount of data they must consider from newer areas like ESG, added to a growing number of external inputs, means there is just more to consider than ever before. In our global survey, most of the CEOs report that they still rely prominently on operational data (76%) and financial data (75%). Yet more than three out of four CEOs stress that the most important decisions cannot be made on data alone. In fact, 63% of the CEOs turn to input from their people, and over half (54%) include personal experience and intuition in the mix
Cyber security
CEOs need to rely increasingly on their Chief Data Officers (CDOs), as decisions about data and cybersecurity multiply. Six out of 10 (61%) CDOs said their organizational data is secure and protected, but they also shared that they struggle with data management issues such as reliability (47%), regulatory barriers (37%), unclear data ownership (36%), and data siloes/lack of data integration (33%)further complicating protecting data and privacy.
AI Management
To get ahead of this wave, top CEOs are initiating and deepening conversations with their teams about the use of AI—to both remove roadblocks to progress and to ensure safety measures are in place and promote responsible AI. They need guardrail that align with the organization’s values and standards. They also need team members who have AI skills. “Acquiring digital experts is one of biggest challenges.
Top CEOs should prioritize to elevate decision-making in the age of AI.
1. CEO leadership
- Data and technology drive for participants
- Prioritize the business goals and reduce the risk of return
- Have plan and Maneuver approach for business models and for-casting
2. Metrics and decision-making
- Transparency between data source and decision maker
- Distributed workflow with active participants in decision making
- Data management, data reliability, regulatory factors, data ownership, and data integration by Chief data officer
- Roadmaps for profitability and durability
3. Talent and workforces
- Potential impact of generative AI on your workforce
- "Numero Uno" a digital solution based on efficiency, skillset by participants
- Talent hunt and competitiveness for generative AI to outsource
4. Technology and data
- Discovered AI as integral AI within the system for generative AI: prioritizing data lineage and provenance, customizable proprietary data, and crucial data security
- Organizational architecture should synchronize for Prioritize applications where AI can boost competitiveness, innovation, and unique business value
- Accelerate transition to zero-trust security across the enterprise and partner network
5. Ecosystem
- Build a common platform using open hybrid technology that is consistent, scalable, and optimized for the organization and partner ecosystem.
- Make reliable, secure and durable eco system with collective force and common goal
- Make a winning team to create landmark