Weighing the Risk and Reward of AI: A Non-Technical Guide for Business Leaders

ABSTRACT: Business leaders can address AI bias and use it to have rational discussions about management and human bias.

During CDM Media’s September 2023 Houston CDO and CIO/CISO Summit, I joined a group of business and IT leaders across various industries to share perspectives and best practices. I also participated in an executive dinner and roundtable to focus on Artificial Intelligence (AI), hosted by Advansappz. There is a general sense that while most organizations have not yet fully embraced or understood AI, we are at an inflection point. Some organizations want to become AI change leaders, some innovators, and others cautious optimists, but everyone expects that they will have to do something eventually to move up the adoption curve.

Thanks to a diversity of experts in the audience, we heard many points of view that others haven't considered. Since most attendees have IT or analytics backgrounds, we are supposedly more informed than other business peers. Yet it was concerning to observe that even among this group, we still grapple with the same fundamental questions, issues, and challenges concerning AI. Everyone is looking for a common and practical framework for non-technical business leaders to make fully informed decisions on the risks and rewards of AI.

AI Risk and Reward

An organization should not be quick to adopt AI, especially Gen AI, for many reasons. This new type of AI, perhaps more than predecessors, can inadvertently violate privacy, amplify bias, and lead to incorrect conclusions or information. Given its novelty, not all risks are yet known and measurable, and there's no clear regulation to govern it. Two risk characteristics of Gen AI are particularly problematic: the difficulty in explaining models and the hallucination problems (where an AI output seems believable to humans even when it is false). These raise the question of AI trustworthiness.

Others believe that they should fully embrace Gen AI because the potential benefits will be significant and disrupt traditional business models. Gen AI can improve internal process efficiencies by an order of magnitude. It will unlock new insights to increase market reach and improve product quality exponentially. And even though there are still significant risks and compliance issues to consider, the ease of access and public fascination with Gen AI creates a fear of missing out (FOMO) effect.

Whether, when, and how an organization should allow or adopt AI are not one-size-fits-all questions. The answer depends highly on industry, organizational maturity, risk appetite, and applicable regulations. Regardless of the company's current position on AI, everyone agrees that, eventually, every company will come to adopt AI and that the most prudent thing to do is to prepare by investing in data governance, security, and privacy capabilities.

Senior Management and Board Questions

The consensus among business leaders is that AI, especially Gen AI, is beneficial to nearly every business function in every industry, although the use cases and degree of benefit will vary. Despite the immense AI risks with privacy, bias, and security, the labor savings and economic benefits of large language models are real and readily demonstrable. As a result, there is a growing sense that the commoditization of Gen AI is inevitable.  What top-of-mind questions are executive teams and their boards asking, or should they be asking, as they try to determine the strategic impact of AI for their organizations? Here are the common themes that we gathered from the roundtable group.

1. Can AI bring transformational benefits to my organization? How will it change my industry and competitive landscape?

Because AI needs a significant amount of training data as fuel, AI will benefit the companies that can have the scale and capability to manage big data. This includes companies such as FAANG (Facebook / Meta, Amazon, Apple, Netflix, and Google / Alphabet) and other technology leaders. Even for large enterprises outside of technology, this is a tall order. For small and medium companies, it seems even less likely that they can reap enormous benefits from AI. Furthermore, AI may alter the competitive landscape to gravitate to a monopolistic or oligopolistic structure. In every industry segment, it will favor the fewer and larger firms that can gain dominance in consolidating data and analytical capabilities.

AI benefits will favor the few larger firms that can gain dominance in consolidating data and analytical capabilities

Hence, the more relevant question for the board and executives is this: In a future where AI will become pervasive, what business model and operating framework will enable us to capitalize on it? What can companies do to stay competitive? One area worth consideration is "Privacy-Preserving Data Sharing and Analytics" (PPDSA), a national strategy proposed by the White House Office of Science and Technology Standards in March 2023.

PPDSA includes techniques such as differential privacy, homomorphic encryption, synthetic data, secure multiparty computation, and federated learning. They allow companies to explore, use, and share data securely and privately—without giving it away—in a raw, readable, and reusable form. Organizations can create partnerships and data marketplaces to enrich their training data, enabling them to produce AI models that have far greater stability, accuracy, and confidentiality. PPDSA allows all organizations to increase speed and scale to discover and access training data for AI. It has the potential to help smaller and medium enterprises compete against the big data incumbents. 

2. Does my organization have what it takes to implement AI and drive proper adoption?

According to a survey by IBM, a majority (~75%) of the chief executive officers believe their organization is ready to embrace Gen AI, but only 29% of senior or middle managers think the same. The reality is that most organizations are behind and have much room to improve their people's AI skills. Many companies took smaller steps and aimed for quick wins, such as creating a data literacy program or a center of excellence.

Even if an organization does not yet have senior executive buy-in to invest in AI, employees are hungry for education and skills development in AI. Investment in data and AI training would increase your employee's satisfaction and keep your top talents. Those who do not invest in AI education risk losing talented team members and keeping unmotivated members.

Those who do not invest in AI education risk losing talented team members and keeping unmotivated members

3. How should I prioritize and synergize my effort to address AI with other strategic risks?

Indeed, issues such as cybersecurity should be on top of mind for boards and executives. But they are not mutually exclusive with AI. As mentioned above, privacy-preserving data sharing and analytics (PPDSA) technologies can help strengthen your cybersecurity posture while enhancing your ability to win with AI. PPDSA techniques involve an intersection of risk, data science, and analytical skills. They might prove a great way to promote cross-collaboration and knowledge transfer between your risk and data teams. 

Investing in PPDSA education and solutions will help your cybersecurity, risk, governance, and compliance teams improve their analytical acumen. In addition, your data science and business intelligence teams will gain a higher appreciation for risk and compliance frameworks as they work on PPDSA initiatives. Such efforts can catalyze conversations at the board and executive governance level to address cybersecurity and AI in a unified platform. 

AI also offers an opportunity to stimulate and educational discussions of bias and fairness. Many of the fundamental root causes of machine learning bias are congruent with and analogous to human bias. Such root causes include invalid assumptions, lack of data, untested hypotheses, and flawed interpretations. Business leaders can approach the topic of AI bias and use it as a springboard to have scientific and rational discussions about the issue of management and human bias. At a time when issues such as diversity and inclusion can be polarizing in companies and industries, this can be an effective tool.

AI offers an opportunity to stimulate educational discussions of bias and fairness


In conclusion, AI must be explored with the utmost care at the highest level of corporate governance. Whether your executive team is in the pro or the con camp, you have nothing to lose and much to gain from choosing to elevate and tackle the topic head-on. The debates around AI will push organizations to improve their cybersecurity and privacy controls. It will also drive waves around talent development and employee engagement issues. The only losing position is choosing to bury our heads and not face the issue of AI with boldness.

David Hendrawirawan

David helps clients architect data lakes, optimize BI reporting practices, automate data quality and master data management, and engineer cybersecurity, privacy, and responsible AI/ML controls. Having previously been with...

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