LIVE_AI in Professional Services

What’s your organization’s level of data analytics maturity?

Maturity levels for data analytics advance from hindsight only (often due to siloed or inaccessible data) to descriptive (data for reporting and dashboards, some predictive ability through advanced analytics) to foresight/prescriptive (data helps set strategy and data analytics are embedded into decision-making). It is now crucial to understand where you are on this spectrum in order compete for the right leaders who can help you make the most of your data through AI as well as other technologies, and to elevate data to the C-suite, in the context of a growing set of high-impact AI/data use cases.

Not surprisingly, our conversations with many clients reflect this new technology-driven reality. Based on those conversations, here are five questions we think are most critical to ask:

If you are a leader in consulting, law, audit, or other professional services, AI is fast becoming part of how your business operates and serves clients.

If you are a leader in consulting, law, audit, or other professional services, AI is fast becoming part of how your business operates and serves clients. Consulting firms are investing billions of dollars in AI1 and looking to hire more AI-focused talent and leaders. We’re seeing this firsthand through our work, for example, in the rising number of searches for chief AI officers. These leaders will oversee a workforce with greater AI capabilities as services businesses train their employees on these new technologies—PwC and IBM2 are both actively engaged in this kind of reskilling, for example. Moreover, AI-based service offerings have already been rolled out in many of these spaces, including tax and accounting.3 Based on these fast-moving developments, we believe AI will soon be part of every offering and process within and across professional services firms, from strategic use internally to deliver services more effectively and cost-efficiently to new offerings to standing up a dedicated practice to help clients harness AI to create value. In short, incorporation of AI reflects the new normal, and it’s not a matter of whether your firm will integrate AI but when and at what depth. Making AI work for you is critical to develop and maintain competitive advantage. But our recent surveys suggest most tech executives see their businesses as comparable to their peers on AI effectiveness, at best.4 As for professional services partners, when asked about the top external factors influencing their outlook for the upcoming fiscal year, AI was consistently in the top three, regardless of whether respondents had an optimistic, neutral, or pessimistic outlook.

Again, this can range widely, with potential leadership of AI strategy by the CEO, AI leader, CTO or chief information officer, executive committee, or others. However, in our experience, most companies do not have a formal, dedicated AI leader. We think it’s critical to have a C-level leader with responsibility for enterprise-level AI strategy, regardless of their title. At the same time, resist the temptation to place AI under an existing top executive’s remit without ensuring they have the knowledge and capability to lead proactively in this area. Moreover, our recent survey of CEOs and board members worldwide shows that AI is increasingly important to boards: When asked about the topics on which the board has most increased the amount of time they spend, the most frequent topic named—by 71% of respondents—is emerging technologies, including AI.5 But most leaders still don’t think the board knows enough: our most recent survey of data, analytics, and AI executives found that nearly a quarter do not believe the board has the knowledge or expertise to respond effectively to presentations on AI.6 In this context, the AI leader’s exposure to and relationship with the board will vary, based largely on how much the business prioritizes AI and data maturity. For example, the AI leader may present to the board (or its tech committee), prepare materials for the board for others to present, or have less exposure to the board directors. This also raises the question of the board’s knowledge of AI, at collective and individual-director levels. We observe that most boards are still evolving to be able to handle AI-related issues/decisions, and gaining AI-savvy board members has become a priority for most businesses.

Who should lead your AI strategy? What’s their exposure to the board?

There is not only a lack of consensus on who leads AI, but also on where the AI organization fits into the broader structure. Where will the data/AI team reside? This group can be part of the technology function or the business, reporting to a CTO, chief AI officer, or business line leader. Naturally, the choices and options involve trade-offs. For example, having a chief AI officer or chief data officer oversee that area elevates data analytics as a key business priority, whereas having data/AI teams report into the CTO creates strong alignment with the tech organization. The latter structure may be especially critical for the build phase of data capabilities but may make the area be perceived as less of a business priority by non-tech stakeholders. In short, think about where your business is on its AI journey and what its current AI-related priorities are to make the right structural decisions for you. Our 2023 survey of data, analytics, and AI leaders found that respondents report to varying senior leaders within their companies, most often the CDO, CTO, or CIO or the CEO. However, in 2023, far fewer respondents said they report to the CEO and far more to the CDO, CTO, or CIO, than in 2022. We look forward to publishing the results of our 2024 survey this summer.7

Getting AI right in professional services is largely about strategic collaboration. For example, it makes sense to prioritize having AI experts work with functions where AI can create the most value. It also helps to develop broad cross-functional knowledge to enable leaders to understand the business as a whole and recognize where to move AI talent where it’s needed most. Finally, consider retaining on-demand AI-savvy executives or project managers when supply of this talent is low in priority areas.

Do you have the right organizational structure to harness data and AI?

What are the considerations for hiring AI leaders?

What can your functional leaders do to develop your organization’s AI muscle?

AI's impact on professional services:

5 key questions every executive must ask

Conclusion

Read last year’s 2023 Data Analytics AI report

About the authors Gustavo Alba is the global managing partner of the Technology & Services Practice; he is based in New York and Miami. galba@heidrick.com Ryan Bulkoski is a partner in Heidrick & Struggles’ San Francisco office and global head of the Artificial Intelligence, Data & Analytics Practice. rbulkoski@heidrick.com

Overall, we know these are tough questions that require thoughtful answers in a large, evolving space, and at a time when there’s fast-rising demand for global AI talent. We hope this overview helps you ask the right questions and generate thoughtful answers to them, wherever your organization may be on its AI journey.

5 questions for executives

Tim Paradis, “AI in consulting: Firms are racing to implement artificial intelligence,” Business Insider, October 4, 2023. “IBM Commits to Train 2 Million in Artificial Intelligence in Three Years, with a Focus on Underrepresented Communities,” IBM Newsroom, press release, September 18, 2023. “How AI transformed the tax and accounting profession in 2023,” Thomson Reuters Tax & Accounting, January 8, 2024. For more, see Ryan Bulkoski and Frédéric Groussolles, 2023 Europe and US Data, Analytics, and Artificial Intelligence Executive Organization and Compensation Survey, Heidrick & Struggles. Board Monitor US 2024: Naviagting shifting sands, Heidrick & Struggles, May 20, 2024. Ryan Bulkoski and Frédéric Groussolles, 2023 Europe and US Data, Analytics, and Artificial Intelligence Executive Organization and Compensation Survey, Heidrick & Struggles. Ryan Bulkoski and Frédéric Groussolles, 2023 Europe and US Data, Analytics, and Artificial Intelligence Executive Organization and Compensation Survey, Heidrick & Struggles. Heidrick & Struggles proprietary data from a survey of 285 technology & services industry executives conducted in May 2024. Heidrick & Struggles internal analysis of proprietary data.

Businesses are finding their way through the AI talent terrain. We recently surveyed leaders across technology and services firms and found that, when asked what challenges, if any, their company is having in building AI expertise, more than one-third said that there are too few people with AI expertise available at any level. As for how they are building AI expertise, 76% said they are developing that expertise internally, 54% said they are collaborating with external partners and vendors, and only 33% said they were hiring full-time leaders. We’re also seeing a majority of appointments from outside the company, but 75% of those are from within the same industry.9 Key attributes sought in AI leaders include tech and leadership competencies, sector experience, and past success with digital transformation. Companies looking to recruit AI leaders also face questions and trade-offs related to geographic sources. For example, the West Coast talent pool is deepest but is largely experienced in the tech sector and has the stiffest competition (and the highest compensation requirements). Meanwhile, those with East Coast experience tend to be more affordable but may bring a potentially less entrepreneurial mindset and way of working.