With the rapid implementation of artificial intelligence (AI) across the government and commercial sectors, much of the focus has been on the procurement of AI technology and the impacts to the workforce, notably task efficiencies, job displacement and the need for rapid upskilling of related competencies. There is, however, less discourse on how this new technology impacts those who are leading and managing the employees who are charged with using it. How is AI affecting leaders? What challenges and risks do they face? How do organizations prepare leaders and managers to guide the workforce in the adoption of this new technology?
The implementation of AI poses several leadership challenges. These challenges can be broadly summarized into four areas: (1) governance, compliance and security, (2) board engagement (3) decision making, and (4) and managing AI adoption with the workforce.
While there are certainly many opportunities in the adoption of AI (increased efficiencies completing work tasks as an example), there are also huge risks. Increasingly, organizations are faced with challenges such as protecting intellectual property, privacy, as well as protecting against customer data security breaches, just to name a few. The protection of customer data is crucial for sectors such as financial services and healthcare, as a data breach can have a huge impact on a company’s brand, customer trust and loyalty, as well as create a host of liability issues.)
The primary question each organization must ask is, “How do we balance the opportunities for leveraging AI technology with mitigation of associated risks?”
Organizations in the commercial and Federal sectors are responding in a variety of ways. First and foremost, organizations are taking a hard look at their governance structures and frameworks.
One of the most effective governance approaches is one where there is a shared responsibility among the C-Suite: the CEO, Chief Legal Officer, Chief Financial Officer, Chief Information Security Officer, CIO, Chief Technology Officer and V.P. of Sales or Marketing. A working group comprised of these individuals not only allows for enterprise-wide visibility of potential risks and vulnerabilities, but also provides a forum for different perspectives on how to best balance these risks and vulnerabilities with the pursuit of opportunities.
For example, the CISO or Chief Legal Officer will most likely focus on risk mitigation, while the CTO or V.P. of Sales/Marketing will be looking for ways to take advantage of AI applications to empower engineers, scientists, systems programmers, and customers. Shared governance helps an organization have a balanced perspective on how best to adopt and govern AI.
Furthermore, a shared governance framework puts teeth into AI related policies and procedures. This model demonstrates to employees and stakeholders alike that there is alignment from the top of the organization.
Because data is such an integral part of AI, many organizations are adding the role of Chief Data Officer to this framework. This role helps organizations define how the data is owned and accessed, the inputs and prompts, the data sources, and often negotiates the terms of service with various AI providers. And in response to the Office of Management and Budget’s AI Memorandum M-24-10 (OMB) Federal agencies are creating the role of Chief AI Officer to lead AI governance, compliance and security related initiatives.
In the commercial sector, boards are becoming more active in AI adoption. They are engaging early with the C-Suite about developing a responsible AI framework and reviewing it to ensure alignment with the company’s strategy, objectives and risk tolerance.
Boards are also asking for the creation of clear KPIs and reporting mechanisms to gauge how best the framework is being adopted. In this way, Boards can be communicated to and kept apprised of any concerns or risks.
Some boards also push for ethics counsels and advisory councils, in the interest of ensuring companies are using AI with integrity and fairness.
And finally, Boards are asking the C-Suite to articulate how they are preparing managers and employees to embrace AI. In short, what’s the approach for upskilling employees? How are managers being engaged in the roll-out and implementation of AI?
These practices are also being adopted by Federal agencies, in part, as a response to OMB’s M-24-10 Memorandum.
AI has implications for executive decision making. The key point is, is AI an advisory source to the ultimate decision-maker or do leaders grant decision-making power to AI? For example, Netflix and Amazon don’t keep a human in the loop for movie or product recommendations, but the Department of Defense (DoD) does keep humans in the loop in a kill chain. There’s a vast amount of gray area between those two scenarios.
Many uses of AI create decision making opportunities and each of these opportunities needs to be scrutinized…and as part of an overarching governance structure, policies and guardrails need to be developed so that an organization doesn’t unwittingly let a potential flawed AI make important decisions.
As with any new technology, employees often fall into three camps: those who are eager to use the technology (early adopters), those who take a “wait and see” approach, and those who are reticent. Successful leaders are well aware of the different levels of receptivity and know how to engage each group. This is often one of the areas of keen interest to Executive Boards. Without the appropriate outreach and communications efforts, the adoption of AI will be slower than desired and, thus, will ultimately impact the desired ROI and related outcomes.
AI adoption presents many unique (and some not so unique) challenges that executives in the commercial and Federal sectors need to address. Beyond the procurement of AI technology and employee upskilling, leaders need to focus on implementing shared governance, compliance and risk frameworks, actively engaging their Boards, understanding how best to leverage AI for decision-making, as well as proactively engaging stakeholders, managers and employees.
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A woman’s hand is asking an AI chatbot pre-typed questions & the Artificial Intelligence website is answering.
It’s clear that AI is a major “technology disruptor” and has introduced uncertainties for many organizations. These uncertainties have future implications for leadership as well as the workforce. At Toffler Associates, we have a long history of helping organizations prepare for uncertain futures. Through our Futures and Foresight approach, we help organizations better understand the future of work and how to develop strategies to prepare leadership and employees for uncertainty. For more information, see our white paper on The Top 9 Future of Work Disruptors Guide (tofflerassociates.com).
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