(Part 2) The Winning Talent Strategy for 2025 and Beyond: Harnessing Talent Intelligence for Leadership, Succession, and the Future – Interview with Toby Culshaw

PART 2

Part Two of Margaret Jaouadi’s conversation with Toby Culshaw explores how organizations can utilize data-driven talent intelligence to shape executive succession, strengthen leadership pipelines, and prepare for the next wave of HR innovation.

As organizations deepen their understanding of data-driven talent intelligence, the conversation naturally shifts to its strategic applications at the highest levels. In this second part, Toby Culshaw and Margaret Jaouadi explore how talent intelligence is transforming executive succession planning, leadership pipeline development, and the vital collaboration between talent intelligence, executive research, and executive search.

They also tackle the growing influence of AI and automation, the challenges of upskilling talent professionals, and the emerging technologies set to redefine the future of talent strategy. Through practical examples and candid insights, Toby Culshaw provides actionable guidance for organizations seeking to develop and scale a robust talent intelligence capability.

Margaret Jaouadi
Given what we’ve discussed about skills-based models and internal marketplaces, how does this apply to senior leaders? We often hear that career progression at senior levels involves taking on stretch assignments and moving across departments to gain a broader business perspective. How do you see these approaches aligning with the new talent intelligence and skills-based frameworks for executive roles?

Toby Culshaw
That’s a great question. The expectations for leadership are changing. We’ve seen a shift from traditional leadership focused on command and control—where the emphasis was on operational efficiency rather than setting a long-term vision—to a much more dynamic, multi-faceted role.

What’s interesting is how this evolution connects with both internal talent marketplaces and external talent intelligence. Internally, as you mentioned, it’s about proactively moving people across the business to give them the experiences and skills they need before stepping into leadership roles. This approach helps build a pipeline of well-rounded, adaptable leaders.

From an external perspective, talent intelligence is all about understanding how your organization compares to competitors. If you don’t have a robust internal succession plan, you need to know what’s happening outside your walls. For example, suppose you want to hire a leader with international experience, but your main competitors are strong national players that tend to promote from within their region. In that case, you might struggle to find the right fit externally. Their philosophy and talent pool might not align with your needs.

In such instances, talent intelligence becomes closely aligned with executive research. The lines start to blur, and you end up overlapping with competitive intelligence as well. Are you hiring to fill a succession gap, or are you looking to disrupt the market? Sometimes, you might even acquire entire teams or organizations for their skills, not just individual hires. We’ve seen this in high-profile cases, such as when companies have acquired top talent and their teams to drive innovation or enter new markets.

Ultimately, talent intelligence is about understanding both your internal capabilities and the external landscape, enabling you to make informed decisions. Whether that’s nurturing internal talent, targeting specific external hires, or even acquiring entire organizations to drive change, the future is about bringing all these pieces together to build a truly agile and forward-thinking leadership team.

Margaret Jaouadi
What role does talent intelligence play in executive succession planning and leadership pipeline development?

Toby Culshaw
Talent intelligence starts to overlap with executive research, and things can get a bit murky when we start talking about succession planning, especially since definitions can vary from company to company. If a company has a strong executive recruitment or research team, it’ll typically handle advanced talent mapping, competitor analysis, and even look at competitor succession planning. They’ll track who’s where, forecast movement over the next 12 to 24 months, and identify key individuals for future engagement.

If a company doesn’t have this capability, that’s often where talent intelligence teams step in. As a rule of thumb, I usually say that if you need personally identifiable information, such as names and contact details, you’re probably looking for an executive research or sourcing team, not just a talent intelligence function.

From an operational perspective, when I led both teams at Philips, the distinction was clear. Talent intelligence focuses on understanding how a competitor’s organization is structured: where the functions sit, how they interact, what the spans of control are, and where the power base lies. It’s about seeing the business at a functional or systemic level, how things operate regardless of the individuals involved.

Executive research, on the other hand, goes a level deeper: it’s about identifying the specific person in a role. That’s the granular difference. For succession planning and leadership pipeline development, talent intelligence gives you the big picture—how the business works and how roles are designed—while executive research drills down to the individuals who could be candidates or successors.

That said, the lines are blurring. More roles now combine elements of both—executive recruiters or researchers with talent intelligence skills, or sourcers who handle both systemic and individual-level analysis. As a result, you’ll see more hybrid roles where the same person is doing competitor analysis, long-term planning, and succession planning. It’s all becoming shades of grey, but the core distinction is that talent intelligence is about systems and operations, while executive research is about the people within those systems.

Margaret Jaouadi
You mentioned executive researchers and executive search firms, as well as the role they can play. If talent intelligence provides an overview of how competitors operate and how their processes work, how do these teams then collaborate to identify specific individuals for executive roles?

Toby Culshaw
It’s a crucial partnership, and its implementation varies from company to company. Some organizations possess these capabilities in-house, while others outsource them to external firms. What’s interesting is that executive recruitment firms are expanding their offerings—they’re moving into talent intelligence, location strategy, competitor intelligence, and design benchmarking areas.

The evolution is pretty organic. The skill sets within talent intelligence are also broadening. While most talent intelligence professionals come from talent acquisition, executive recruitment, or executive research backgrounds, you’ll also find people from marketing intelligence, economics, business intelligence, and analytics. The field is becoming much more diverse.

Executive research, on the other hand, remains a more specialized skill set. These teams often conduct primary research, reaching out and speaking directly with individuals to gain a deeper understanding of their needs and concerns. Talent intelligence teams, by contrast, usually don’t interact directly with candidates. Instead, they collaborate with executive researchers or local recruiters to get the “voice on the ground.” The talent intelligence team might inform the plan, but it’s rare for them to be the ones making direct contact.

Overall, it’s about leveraging the strengths of each function: talent intelligence provides the big picture and strategic insights, while executive research and search firms focus on identifying and engaging with specific individuals for executive roles. Together, these teams create a more comprehensive approach to executive hiring and succession planning.

Margaret Jaouadi
People might think: “I don’t need Talent Intelligence because AI is going to provide all the information I need.” What is the answer to that? You’re smiling.

Toby Culshaw
It’s a great question, and I’m smiling because we’re running a competition in the Talent Intelligence Collective right now around prompt engineering: Can you create a location strategy just from a single prompt? It’s fascinating.

Do I think AI will have a massive impact on talent intelligence? Absolutely. Do I believe there are risks? Definitely, for most talent intelligence teams, who are often underfunded and overworked, AI and new tech tools are a huge help, scaling their work and making it more efficient.

However, my concern is that too many people will take AI output at face value, without questioning the data or consulting secondary sources. That’s a real risk, especially since AI is designed to please you. It can hallucinate, cherry-pick data, or even make up facts to give you what it thinks you want. That’s why it’s both hugely powerful and potentially dangerous.

I believe the future will be about utilizing trusted, curated data sets, such as those provided by firms like Litcos, and then running generative AI tools on top of that. That way, you’re leveraging AI’s power while keeping things grounded in reliable data.

We’re also likely to see more “copilot” chatbot interfaces, such as Microsoft Copilot or Google Gemini, integrated into everyday workflows, allowing recruiters to access intelligence and research at their fingertips without needing to switch between tools. That’s where I’d want my intel and research to be: seamless and integrated.

We’re still in the early days, perhaps Generation 1.5, so it’s both exciting and a bit terrifying. There are already significant changes: AI can do sourcing and executive research much faster and at scale. But the real challenge isn’t identifying people or skills that have been easy for years. It’s getting candidates to commit and getting them to open up. That’s where things are getting harder.

The real value will come from human interaction and validation—getting researchers out to conferences, networking events, and engaging with people. Identification is easier than ever, but building genuine relationships is where the true power lies.

Margaret Jaouadi
I’m sure that many people at my company, when they read this, will stop worrying about being replaced by AI.

Toby Culshaw
I think that’s the key; it’s about being clear on the unique value you bring. When people reflect on their jobs, most want to contribute something meaningful. Very few want to be just an aggregation service, churning out lists of names in Excel. Being used as a human aggregator is not especially rewarding for most people.

What matters is adding value, whether that’s through insight, relationship-building, or strategic thinking. For most people, the shift toward more value-driven work is a positive change. However, it is a significant change, and for some, it can be a bit intimidating. Ultimately, though, it’s about focusing on where you make a real difference in your role.

Margaret Jaouadi
Upskilling talent acquisition professionals on new technologies presents a significant hurdle for many companies. It’s not as simple as asking ChatGPT for information. You need to know what to ask, how to interpret the data, and how to question its validity. As you mentioned, you can’t just accept the output at face value. How do you equip the teams to use these tools effectively, rather than just being satisfied with quick answers that AI can provide in seconds?

Toby Culshaw
Absolutely. The root problem is that the education system in most Western economies primarily focuses on rote learning and repetition. This model was designed during the Industrial Revolution to train people to follow instructions and avoid machinery accidents. It hasn’t evolved, and it’s gotten worse: education now prioritizes exam-passing over genuine learning.

That’s terrifying because it strips away critical thinking and creative problem-solving, precisely what we need now. We treat textbooks and exams as gospel truth, but with AI, we must default to a more skeptical approach. Assume the output is wrong until you validate it. This shift demands retraining: teaching people to dig into data, challenge assumptions, and verify sources.

Here’s the irony: the professionals who could scale this work with AI often don’t want to engage in critical analysis. They’re looking to automate the very tasks we’re asking them to master. Users who require a high level of strategic and consultative thinking often resist this aspect of the job. It’s going to be fascinating and challenging to see how this tension resolves.

Margaret Jaouadi:
Looking ahead, which emerging technologies or innovations will most transform talent intelligence over the next few years?

Toby Culshaw:
Generative AI, such as ChatGPT and Claude, will play a significant role in the picture. However, I believe the real transformation will occur as these systems become more deeply integrated with backend data. That’s where things get interesting, because right now the most significant challenge we face is data silos. We have so many disconnected data sets, and it’s a manual, time-consuming process to try to bring them together and make sense of them.

With more advanced, integrated systems, you’ll be able to use intelligent agents to overlay different types of data, like your compensation philosophy, attrition rates, performance ratings, hiring trends, and even external competitive data. You can even layer in external factors, such as share price, and combine them with your financial data to see how sales performance is tracking. Suddenly, you can spot patterns and insights that are invisible when you’re stuck in separate silos.

For example, you might discover that when your share price is high, you’re able to hire better quality salespeople faster, and that’s driving real business impact. These kinds of connections between data sets are fascinating, but most teams don’t have the capacity or access to explore them right now.

Operationally, we’ll see all the usual tools, such as ChatGPT and Claude, embedded into workflows, auto-transcribing calls, summarizing meetings, and highlighting key themes in long documents, all without manual effort. All of that will continue to drive efficiency.

But to me, the real value is under the hood: the ability to break down silos and enable pattern recognition across all your data. That’s less flashy than the front-end tools, but it’s where the most significant transformation will happen. It’s an exciting time for talent intelligence.

Margaret Jaouadi
Do you think it will be humans who decide which data to combine to uncover new insights, or will AI itself prompt for and collect the data required to reveal the big picture?

Toby Culshaw
I hope it’s the latter; I hope it’s the AI. The real power of agentic AI lies in its ability to make decisions and explore your data warehouse. That’s where things get exciting: if you allow these agents to look for correlations and causations across your data, they can uncover insights that might otherwise remain hidden.

Our traditional ways of thinking and the questions we’ve always asked limit us. We tend to get stuck in familiar patterns. But with AI, you get a fresh perspective. The agent can ask: “What’s possible here? What are we not seeing yet?” That’s what makes this so fascinating – the potential for AI to reveal new patterns and opportunities that we might otherwise miss.

Margaret Jaouadi
To wrap up, what practical steps can organizations take to incorporate talent intelligence into their talent decision-making? Can you share three practical tips or key actions for companies to consider?

Toby Culshaw
First, start by using the data you already have. Most organizations have mountains of data in their ATS, CRM, and other systems. You don’t need a considerable investment to get started. Dig into those red flags and outliers I mentioned earlier. Identify the pain points and find some proof points to demonstrate value.

Second, run pilots and experiment with different types of analysis. Some companies will prioritize competitor intelligence, while others will focus on talent flow analytics or sentiment data. Discover what matters most to your organization and focus your efforts accordingly. Don’t try to do everything at once; see what works and what doesn’t.

Third, as you start to see value, build a business case for dedicated resources. Often, talent intelligence begins as a side project within sourcing or executive research teams, but as the work grows, you’ll need specialist headcount or at least dedicated capacity. The problems you’re solving, like manufacturing transformations or large-scale workforce planning, are often far removed from day-to-day recruitment. Demonstrating the ROI and explaining why this work is critical to the business is essential.

If you’re lucky, senior leadership will bring in a consulting firm to get this kind of insight before making big decisions. But if not, they’re making those calls blind. Most executives don’t even know this data exists, because as TA and executive search professionals, we’ve been too good at keeping it to ourselves. Once you start showing what’s possible, the demand will follow.

In short: invest in talent intelligence. If you don’t, it’s like running a Formula One team without an R&D function. You might save money in the short term, but when the market picks up, everyone else will be racing ahead while you’re left behind.

Margaret Jaouadi
To close, can you share a specific example of a company that invested in talent intelligence and the practical outcomes it achieved, or what happens when organizations ignore talent intelligence insights?

Toby Culshaw
Let me start with a cautionary tale, because it’s often the most instructive. I once worked with a global business services company on a location strategy for a contact center. We analyzed 22 potential locations and ranked them based on access to talent and other critical factors. One particular city ranked 18th, and we explicitly advised against opening there. We said, “This is a terrible choice. Do not go to this place.”

However, the company disregarded our advice and chose that location because it was cost-effective. Two years later, they had a major staffing problem and had to escalate the issue up to the CHRO. When we revisited our original recommendations, it was clear: ignoring talent intelligence had cost them tens of millions in infrastructure, lost productivity, and more. This costly example became a huge validation point for the organization, leading them to invest more seriously in talent intelligence and establish standard methodologies for future decisions.

On the positive side, when companies do invest in talent intelligence, they can avoid these costly mistakes. They can make informed location decisions, conduct practical competitor analysis, and address talent flow issues before they become problems. However, the challenge is that the value of talent intelligence is often in preventing future pain, so the business doesn’t always feel the immediate benefit. It’s similar to cybersecurity: organizations usually only invest after a significant incident has occurred.

Unfortunately, businesses sometimes have to experience the pain before realizing the importance of investing in talent intelligence. It’s a harsh lesson, but a crucial one for long-term success. Real-world examples from other organizations, such as those that have reduced time-to-hire or improved talent quality, demonstrate what’s possible when incorporating talent intelligence.

Margaret Jaouadi
Thank you, Toby, for this all-encompassing conversation and for bringing clarity to this critical but often misunderstood topic.

For a confidential chat about how Pacific International can assist you with your Talent Acquisitions and Diversity challenges, please contact Manuel Preg or one of our Executive Search Consultants specialising in your sector.