What AI could mean for talent across the C-suite

AI is here. It will impact you no matter your sector or function, as its capabilities are growing exponentially. By some estimates, 100% of organizations will be using AI by 2025.

But the impact will vary markedly across areas. The important questions for C-suite leaders, then, are specifically where and how generative and other forms of AI will impact your function, business, and industry? How to invest in it appropriately and plan for the future given the obvious value-add and potential risks? In this article, we present insights on these questions from our own leadership and the markets we serve across sectors.

Themes across all functions include:

• Augmentation, not replacement: It’s about using AI for augmentation rather than replacement of decision-makers and decision-making processes. So think of AI as a tool rather than a full solution in and of itself.
• Advance with caution: AI is like a mirror that reflects us fully as a society, including biases and discriminatory practices, so be aware of these rather than blindly accepting what AI offers. Also, recognize and be sensitive to the reality that AI will disrupt some jobs and change some roles, as it already has.
• Build the guardrails: Guardrails are critical here, as is the regulation of AI-based activities. But regulation will come with time, as it has for many other technological advancements in the past, so businesses in the meantime have to figure out ethical and risk guardrails for themselves.
• Track evolution: AI is a continuously evolving space and process. Deciding who in your organization should track related progress and make relevant decisions will be important, as well as thinking through how you communicate new opportunities, risks, and policy changes related to AI to your internal and external stakeholders.
• Relationships and judgment remain critical: While AI will continue to become more trustworthy and optimized, the value of empathetic leaders who support this advancement but continue to value relationship-building will be central to success.

With those themes in mind, consider the implications of AI for each major function represented in the C-suite.

Human resources

Given our focus on leadership and talent, we are seeing multiple AI-driven applications and opportunities in the HR domain. Here are some of the most significant ones.

• Talent assessment: For CHROs, AI could play a significant role in talent assessment, helping analyze data to deliver insights related to high-potential-talent identification within specific functions, roles, and levels inside an organization, which further optimizes pipelines and succession planning.
• Employee engagement: AI applications could quickly synthesize themes from employee engagement survey responses, exit interviews, and other sources to provide a near real-time perspective on not only how employees are feeling about organizational culture and the general employee experience, but also what gaps exist and need to be addressed.
• Risk assessment: Managers could use AI to understand which employees may be at risk for departure based on certain comments or feedback, performance patterns, or even participation in meetings.
• Bias identification: An important area to apply AI is the assessment of existing bias in hiring, promotion, and performance management practices, such as implicit bias related to race, gender, or other dimensions. Of course, the flip side of this is ensuring AI does not introduce new biases.
• Rewards: AI offers leaders the potential to significantly alter how their organizations approach the total rewards function. For example, AI technologies can help write or modify rewards programs using publicly available SEC filings to customize packages for leaders in specific situations (e.g., a public company executive newly hired by a PE-backed business).
• HRIS: AI will likely power the go-to enterprise software and systems HR leaders and teams use to better understand/communicate with their employee populations.
• Organizational design: Analytics tools and models powered by AI could enable CHROs to both test and design solutions against predicted top- and bottom-line impact, and maximize the return on investment for different organizational initiatives. In M&A, AI could be used to predict whether a company is likely to merge, or possibly even ease of integration and challenges that may arise related to culture, org design, and others.

Because of this broad, growing range of AI-based HR applications, CHROs and their teams are increasingly expected to have strong AI acumen. We see this becoming a top priority for our clients across sectors.

Legal and government affairs

Our experts and client executives believe AI represents potential for major enhancement of the legal role and function. Use of these technologies could enhance access to business intelligence and promote better understanding of the business at both strategic and tactical levels. Here are some likely applications and related recommendations.

• Understanding business implications: AI could be used to assess, in seconds, the wide range of business implications of legal matters in local and global markets. Imagine in-house counsel for a manufacturer is reviewing an agreement for sales to push back the start date of a large-scale customer project. In this context, it is not just about making the contractual extension happen but evaluating the impact on all other business units, something rarely done in the past. Specifically, the general counsel can use AI to specify the contract modification and AI will understand major and more subtle impacts to product, manufacturing, supply chain, procurement, sales, import-export, and many other areas.
• Routine task completion: AI offers the ability to complete some of the more mundane tasks in legal, such as document creation and review, affording the legal team greater capacity to partner with the business for more strategic and proactive work.
• Take a collaborative approach to best practices and investments: We believe it must be a true team effort to secure the best results from AI applications. For example, the CIO and general counsel should collaboratively approach possibilities and risks associated with AI for internal and external uses. Companies will need to decide, for example, whether to allow the use of generative AI internally (see more on CIOs later in the article). Some are opening this door while others are more wary, such as a company that may prohibit the use of AI because they see their IP and content as part of their value proposition. Ultimately your top executives should collaborate to decide investments best for your organization, recognizing outside regulation will arrive at some point—for example, most countries offer only AI-related guidelines, but some, like Korea and Italy, are advancing legislation in this area.

Turning from legal to government affairs, AI can enhance policy and legislative advocacy-focused efforts in multiple ways. Examples include:

• Data analysis: AI can support faster, better organization and assessment of information such as public records, legislation, and news articles to use as actionable intelligence.
• Prediction: New digital technologies are highly applicable to forecasting business-affecting policy outcomes and anticipation of other government decisions such as court rulings.
• Monitoring and engagement: Government affairs leaders can use AI for ongoing monitoring of legislative activities, such as automated tracking of bills and committee hearings in real-time, enabling better recognition of opportunity, along with facilitation of timely communications with government officials.

Of course, ethics are critical here, as data and algorithms used in AI-aided lobbying must be transparent and free of bias.

Supply chain

When it comes to supply chain, the impact of AI is part of a decades-long trend toward progressive digitization of smarter, quicker decision-support systems.

Think of AI as shifting decision-making into turbo mode, through large-scale improvement in predictive analytics and process control spanning broader networks of supply chain ecosystems. Specific benefits of the new technologies will be evident in the traditional domains of efficiency and effectiveness but also in greater supply chain agility and resilience. Drivers of these improvements include (1) better visibility with faster access to more data; (2) better execution with more nimble response and control; (3) higher-quality collaboration across partners and networks. 

Here are some of the likely practical applications of AI in this domain:

• Algorithmic decision-making: AI’s data-driven algorithms generate millions of corrective actions fed back into supply chain systems at a speed and scale that humans cannot duplicate.
• Sensing and tracking: AI can power Internet-of-Things remote sensing to track items in transport or warehouses and optimize routes and storage.
• Control and inspection: Computer vision can be used to automate product identification, authentication, and quality inspections for improved compliance and chain of custody.
• Predictive maintenance: AI applications can monitor vehicle engines, factory equipment, and other large CAPEX items to get ahead of required maintenance and prevent costly failure.
• Digital twins: Companies and their supply-chain partners can use digital twins of supply networks to simulate operations under different scenarios for faster intervention and improved resilience.
• Robotics: AI is enabling increasingly smarter autonomous mobile robots (AMRs), automated guided vehicles (AGVs), and other material handling equipment (MHE).

Marketing and sales

AI is viewed as a zero-cost, efficient way to perform key simple marketing tasks, especially for companies on a shoestring budget. There are seemingly endless applications of AI in the marketing and sales domains, including these:

• Writing: Current uses of generative AI center largely around content development, including writing initial ad copy, social media and blog posts, and creative briefs with input and refinement from creative teams.
• Research: ChatGPT, Bard, and other emerging platforms can perform data-rich research, again with input, double-checking, and refinement from marketing team members.
• Creative ideas: AI technologies can jumpstart the creative process for teams as related to advertising, marketing campaigns, apps, and others. CMOs we know have noted that generative AI platforms help their teams come up with great starting points for creative ideas or campaigns, and that access to this “first coat of paint” could ultimately reduce some costly agency work with minimal investment.
• Image creation: Visually focused AI platforms like DALL-E and Midjourney are adept at creating images to be used in creative campaigns, presentations, and other marketing deliverables.
• Product development and innovation: Some of the tasks above relate to product development and innovation in many businesses, such as initial design ideas for new products.
• Sales support: In the sales arena, AI is being used to assess market size, optimize salesforce size, and bridge gaps to customers. It has shown success in improving the ability to sell more with fewer resources and driving increased velocity of closures while improving the quality of customer interactions through sales training platforms that leverage AI technologies.

Finance

In finance and financial operations, too, we and our clients see significant application of and potential for AI, given the large volume of data and predictive analytics or decision-making involved in this space. Here are the evolving applications.

• Forecasting: AI technologies are already driving better forecasts of revenue, costs, and other figures using broader internal and external data, to improve the bottom line.
• Anomaly detection: AI is a powerful approach to anomaly detection in large sets of financial transaction data, for improved fraud identification and security.
• Other analytics: There are multiple other applications of AI in finance, including projecting return on investment, calculating investments required in new products and initiatives, optimizing budgets (especially avoiding underestimates based on past data), and other areas.

Given the high potential for AI in the finance organization, businesses will have to evolve quickly to create tech-enabled economies of scale driven by financial decisions. Finance is already a strong business partner in most companies, but these AI trends will cement this function’s role through advanced, AI-driven analytics. The AI boom will also likely lead to heightened demand for those who bring traditional finance expertise coupled with acuity for machine learning and other AI applications that will power the future of finance.

Technology and information

Not surprisingly, AI is significantly impacting the role of chief information officers (CIOs) and other technology leaders within companies, given they own the technology driving AI, and must work closely with the rest of the C-suite to create strategic opportunities and value. Indeed, companies that fail to leverage AI in a meaningful way will be left behind, meaning technology officers play an even more critical role now. Here are some of the most prominent impact areas to consider in this function:

• Automation and efficiency: AI technologies such as robotic process automation (RPA) and intelligent automation help technology officers automate repetitive and mundane tasks across organizational areas, improving efficiency and reducing costs to enable their teams to focus on higher-value activities. For example, this is critical in the supply chain area, as mentioned earlier; supply chain teams look to technology leaders to help them build the highest-value technology solutions to create bottom-line impact.
• Enhanced customer experience: Technology teams are also responsible for creating, implementing, and managing AI-powered technologies that support and enhance the customer experience, like enabling chatbots and virtual assistants that answer questions and reduce interaction with human representatives; making richer information available to human customer service reps; and providing more powerful personalization/recommendation systems. This is the area in which we see the most activity today, as organizations are using AI technologies to create and pivot the narrative, reach and interact with customers, upsell, course-correct in real-time, and take other actions to benefit customers and companies alike.
• Data management and security: AI applications help technology officers manage and secure data in their organization by detecting anomalies, identifying potential security breaches, and automating threat responses, to meet with and go beyond regulatory or compliance guidelines. While security has always been critical, it will become even more important as AI advances—on both the threat and protection sides—and we are seeing evidence of this as chief information security officers are now sitting on boards of directors.
• Workforce transformation: AI is reshaping the workforce, and technology officers need to lead the transformation. For example, technology leaders are harnessing the opportunity AI gives them to significantly reduce the time it takes to build applications. As another example, technology officers are collaborating with HR departments to address the impact of AI on employee roles and skill sets, and playing a key role in upskilling or reskilling employees to work effectively with and alongside AI technologies, given the revolutionary nature of this shift and the potential displacement it will cause across workforces. They also oversee the ethical use of AI, ensuring transparency, fairness, and accountability in AI-driven decision-making. We’ve been watching HR transformations for decades (which informs the insights we noted in the HR section earlier), but the pace of this change is increasing exponentially now, on multiple fronts, and technology officers are at the forefront.

An evolving, opportunity-rich space

AI is continuously evolving and creating new opportunities—and potential challenges—for all functions. Right now, it’s having the most impact on analytic speed and process efficiency, augmenting human capabilities significantly. But generative AI is fast making its mark creatively.

Leaders must focus on learning and experimentation related to AI, for themselves and their teams. It’s about building collaborative capabilities in this space, while also ensuring an enthusiasm for AI tools doesn’t promote over-reliance on technology (such as for creative processes) or disrupt otherwise thriving cultures and organizations. The idea is to understand AI-related trends and implications and get ahead of these to capitalize on opportunity and mitigate risks.

Wherever you sit in an organization, start having the conversation about how to play in this domain and contribute to your company’s AI and data strategy. In the meantime, watch this space: we are in the process of surveying executives across various functions and sectors, and are excited to bring you more insights and recommendations related to AI in the near future, including our 2023 Data, Analytics, and Artificial Intelligence Officer Organizational and Compensation Survey to be released in Q3 2023.