Close filter
AI Executive Search

Is Your C-Suite Prepared for Artificial Intelligence?

Readiness depends on your organization’s ability to adapt to the transforming talent landscape and willingness to embrace AI integration.

  • June 2023

C-suite leaders face a multitude of compelling challenges when it comes to harnessing the full power of Artificial Intelligence (AI) and its quickly expanding subfield of Generative AI (GenAI)—which is critical to stay competitive in today’s business landscape. These include navigating the complexities of adoption to securing top-tier talent and even selecting an astute leader to strategically steer their organization on this front. 

In this article, we explore how company leaders can deftly navigate these challenges to seize the transformative opportunities that lie ahead. 

A Three-Tiered Process for AI Adoption

AI and GenAI are set to revolutionize every industry by unleashing unparalleled levels of productivity across all areas of business: from streamlining content creation to leveraging predictive analytics for informed decision-making, and more. But the first challenge organizations face lies in adopting these technologies swiftly. Failure to do so may result in loss of competitive edge, while a fast and efficient adoption can provide a significant advantage. 

Adopting AI is not a uniform process. It varies considerably based on organizational capabilities, objectives, and strategic vision. We envision AI adoption as a three-tiered process, with each level representing a deeper and more transformative integration of AI into the business operations:

  • Level 1 marks the initial stage of AI adoption, where AI is incorporated as an additional feature into existing products or services. For example, incorporating a ChatGPT-like chatbot in customer support services to handle routine queries. Level 1 enhances operational efficiency and customer experience.

  • Level 2 entails a deeper application of AI, where it becomes a fundamental component of the business processes by reshaping and improving existing processes entirely. Whether it's automating repetitive tasks, personalizing products or services, improving customer support, or gathering detailed customer or employee insights, AI becomes a key player driving operational improvements.

  • Level 3 marks the zenith of AI adoption, where organizations design new processes from the ground up with AI at their core. With a focus on transactions, AI takes center stage, leading to exponential productivity growth. These processes are typically characterized by higher automation, predictive capabilities, and personalized interactions, all driven by AI technology.

The level of transformation an organization can achieve is directly proportional to the depth of AI integration leaders are willing to embrace. Each level brings a unique set of opportunities and challenges and require different skill sets, resources, and change management strategies. The potential benefits in terms of efficiency, agility, customer satisfaction and business growth that stem from AI adoption, however, are critical to thrive in today's AI-driven world.

Reshaping Talent Strategy

As AI continues to reshape the skills landscape in the business world, how are organizations adapting their hiring and talent engagement initiatives? 

When it comes to hiring, organizations are increasingly prioritizing digital proficiency and AI literacy. They are seeking employees who can go beyond “co-existing” with AI and instead can leverage its potential to yield business results. 

However, as demand for this skill set accelerates, there’s a growing shortage of skilled tech professionals, particularly on AI and at the executive level. The quest for leaders capable of strategically orchestrating AI initiatives and aligning them with business objectives is no small feat.

The shortage of tech-literate talent is causing a shift in the traditional "labor & capital" model. Instead of focusing on tangible assets and technologies ("capital"), the current context places a spotlight on skilled individuals ("labor") – in other words, on employees’ ability to effectively leverage technology. As a result, businesses are prioritizing workforce upskilling and reskilling. Highly sought-after skills include proficiency to navigate AI systems, ability to harness AI and its capabilities, and being able to connect AI usage with business strategy. In this new landscape, competitive differentiation is increasingly being driven by a company's tech-savvy human capital.

When it comes to talent engagement, identifying and recruiting talent on an as-needed basis is no longer sufficient, especially in sectors where the talent pool is limited, calling on companies to develop new approaches. Some of them, as we have seen, include:

  • Employers are exploring a range of alternatives to full-time employment, such as commercial partnerships, advisory roles, and consulting arrangements, to access the skill sets of the limited pool of AI professionals without the necessity of full-time contracts.

  • Companies are adopting the gig economy model in certain instances by offering project-based roles to AI experts. This approach provides organizations access to specialist knowledge for specific initiatives while granting to talent the liberty to undertake diverse, challenging projects without the commitment of a labor contract.

  • Companies are expanding their search globally for AI talent. The rise of remote work and advancements in collaboration technologies have enabled businesses to attract and collaborate with AI experts worldwide.

  • Mentorship and advisory positions are also gaining traction. Companies are involving AI experts in consultative positions, with an additional ability to execute. These AI veterans can offer strategic direction, impart insights based on their expertise, and mentor internal teams, effectively elevating the organization's collective AI proficiency.

To stay competitive in this rapidly evolving world of AI, it is essential that companies focus on being innovative, adaptable, and flexible in their talent engagement strategy. Organizations that can pivot their talent strategies and experiment with new engagement models will be better positioned to capitalize on the opportunities that AI brings.

The Crucial Role of an AI Strategist at the C-Level

Every company should have an AI leader to spearhead efforts. She or he will focus on strategic and transformational aspects rather than solving AI-related issues themselves. This role is often misunderstood because it doesn’t necessarily require deep technical knowledge similar to that of an AI scientist or engineer. While technical knowledge is valuable, it is not the fundamental prerequisite for success.

In their capacity as change agents, AI leaders have the unique ability to guide the organization through the uncharted territories of AI adoption. They must possess a comprehensive understanding of what AI can achieve, its limitations, and the implications for the business. Armed with knowledge, these leaders ask probing questions that can uncover new opportunities for AI application, identify potential risks, and illuminate pathways for strategic AI integration.

Leading multidisciplinary teams effectively is also critical as AI becomes an integral part of various business functions, calling for tighter collaboration between diverse departments and teams. An AI leader at the executive level will orchestrate this collaboration, fostering a shared understanding and vision for AI among team members from disparate backgrounds and expertise.

Another key responsibility of an AI leader is to navigate AI adoption while applying a culture of agility and adaptability: understanding the organization's current state, establishing a clear vision for AI transformation, and charting the course to achieve that vision. This guidance also involves navigating the uncertainties and disruptions that the AI transformation might entail. 

Beyond the strategic, transformational, and team leadership capabilities, a C-level AI leader must demonstrate deep understanding about the ethical implications associated with AI. This includes grappling with issues such as data privacy, security, algorithmic bias, and wider societal impacts. An AI leader must be equipped to navigate these complex ethical landscapes, implementing AI solutions that uphold principles of fairness, transparency, and accountability. Furthermore, they should foster an organizational culture that values ethical AI use by setting clear guidelines and monitoring mechanisms for the responsible deployment of AI. 

Is Your organization Ready for the Transformative Impact of AI?

Your readiness depends on your organization’s ability to adapt to the transforming talent landscape and your willingness to embrace AI integration. By adopting a strategic and preemptive approach to these emergent technologies, you can secure a competitive edge. 

The introduction of AI and Generative AI holds significant implications for businesses. These exponential technologies require a reassessment of established talent management tactics and call for executive leaders to welcome new and innovative talent engagement models. Leaders must comprehend the various stages of AI adoption and evolve into change catalysts capable of leading their organizations into this fresh epoch of productivity and creativity.

Topics Related to this Article

Changing language
Close icon

You are switching to an alternate language version of the Egon Zehnder website. The page you are currently on does not have a translated version. If you continue, you will be taken to the alternate language home page.

Continue to the website

Back to top