Business leaders face a critical challenge: moving past the widespread enthusiasm for artificial intelligence to grasp its practical implications, risks, and strategic value. Two prominent data scientists, Anthony Scriffignano and Inderpal Bhandari, emphasize the need for a measured and informed approach to AI adoption, urging executives to look beyond superficial engagement and consider deeper organizational and financial factors.
Key Takeaways
- Leaders must move beyond superficial AI discussions to real understanding.
- AI offers personal productivity benefits for executive decision-making.
- Industry context is crucial for assessing AI investment risks and opportunities.
- Traditional ROI metrics may not fully capture AI's long-term value or cost of inaction.
- Addressing employee concerns about AI's impact on jobs is essential for successful integration.
Beyond Lip Service: Genuine AI Understanding
Simply mentioning "genAI" in conversations is not enough. Leaders need to understand how artificial intelligence changes the skills required for future success. Anthony Scriffignano, a distinguished fellow at The Stimson Center and former chief scientist at Dun & Bradstreet, highlights this shift.
"Our challenge as leaders is to not just talk about it, but to understand how the skills that got us to where we are today are different than the skills we’re going to need going forward when everything is ubiquitous and discoverable," Scriffignano stated.
This means a fundamental re-evaluation of how work is done and what capabilities are most valuable. The focus must move from simply acknowledging AI to integrating it strategically into operations and skill development.
AI Adoption Fact
According to a 2023 McKinsey survey, 70% of companies report adopting at least one AI capability, a significant increase from previous years, indicating widespread, though often superficial, integration.
AI as an Executive Assistant
At a personal level, executives should view AI as a powerful assistant for decision-making. Inderpal Bhandari, founder of Virtual Gold and former global chief data officer at IBM, explains this perspective.
"An assistant that’s going to come up with ideas based on hidden patterns and data, but something also creative," Bhandari remarked. AI can uncover insights from vast datasets that humans might miss, offering new perspectives and enhancing strategic thinking.
This application of AI can boost the productivity of high-level tasks, freeing up leaders to focus on complex, human-centric challenges that AI cannot yet address.
Industry Context and Investment Risks
Corporate AI investment is complex and highly dependent on the industry. Scriffignano advises leaders to consider their industry's maturity. For nascent industries, AI presents a significant opportunity to lead market creation. In contrast, mature industries face different challenges.
"If you’re in a nascent industry, creating your own market, then absolutely it’s a great opportunity to ride the wave," Scriffignano noted. "But if you’re in a really mature industry where the opportunity cost of sitting out in the wrong direction, some of these genAI initiatives can be extremely expensive, especially long term."
Introducing new AI tools to customers can be costly if the company cannot maintain them. This risk underscores the need for thorough planning and a clear understanding of long-term commitments.
Understanding Opportunity Cost
Opportunity cost refers to the potential benefits a business misses out on when choosing one alternative over another. In AI adoption, this includes the cost of not investing in AI (e.g., losing market share) versus the cost of investing in the wrong AI solution.
Weighing AI Benefits Against Risks
Leaders must balance the promised benefits of AI with its inherent risks. Scriffignano identified several critical areas of concern:
- Misuse: Applying AI in ways that cause harm or are unintended.
- Misappropriation: Using AI to unfairly take or use something belonging to another.
- Misapplication: Deploying AI in situations where it is not suitable or effective.
- Misrepresentation: AI generating false or misleading information.
- Misadventure: Unforeseen negative consequences or failures of AI systems.
These risks demand careful governance, ethical considerations, and robust testing before widespread deployment.
Re-evaluating Return on Investment for AI
Measuring the return on investment (ROI) for AI initiatives is challenging. Traditional financial metrics may not fully capture AI's transformative potential. Bhandari questioned the current emphasis on immediate returns.
"The deeper question is, given that we have these kinds of disruptive technology as we do today, which are going to change the nature of work and the nature of companies, where should things evolve to so that you then have metrics that perhaps go beyond the ROI?" Bhandari asked.
However, he acknowledged the practical reality that CEOs must report to boards on share price. This creates a tension between long-term strategic value and short-term financial expectations.
"Just as a practical matter, if a CEO comes to the board and says, 'hey, I’m now going to be thinking about how to improve the world as opposed to my share price,’ I don’t think it’ll be a long discussion," Bhandari commented.
The Cost of Inaction
Scriffignano highlighted another difficult metric: the cost of *not* adopting AI. This cost is often harder to quantify but can be substantial.
- Marginalization: Becoming less relevant in the market.
- Competitive Moat Shrinkage: Losing competitive advantages.
- Increasing Irrelevance: Falling behind industry standards and customer expectations.
"How do you measure marginalization? How do you measure your competitive moat getting smaller? How do you measure becoming increasingly irrelevant? Those are not things that we have established calculations for," Scriffignano explained. Leaders need to consider these "soft" costs carefully.
Addressing Employee Concerns About AI
Employee anxiety about AI replacing jobs is a significant issue leaders must confront directly. Scriffignano stressed the importance of open communication.
"Part of this is addressing the elephant in the room, right?" Scriffignano said. "If a massive change like this comes about, you don't just put your head down and hope nobody will notice, right? You bring people together, you talk to them, you say out loud what they might be thinking."
Instead of focusing on job displacement, leaders should frame AI as an opportunity to enhance roles and address unmet needs.
"Talk to employees about how this allows us to free up your time, to do something we really need to do, that we can’t afford to hire somebody else to do right now," Scriffignano suggested. This approach can help employees see AI as a tool for personal and organizational growth, leading to a more engaged and productive workforce.
By focusing on how AI can "bigify your job" and address customer needs, companies can foster a positive environment for technological change.
