How AI Could Foster Closer Analyst-Client Interaction, Not Less  

By Giles Alston and Tatia Bolkvadze 

With the emergence of generative AI, the role of geopolitical analysts in consultancies and corporates alike may be about to change significantly. As AI models can now take on some of the more monotonous and time-consuming tasks required of analysts, those analysts are freer to perform increasingly needed person-to-person interaction with clients.  

The evolution of the role has already begun in some quarters, and will probably gain momentum as AI models become more powerful and dependable and boards demand more tailored information obtained from dialogue with analysts. In other words, intelligence and analysis that sets out the implications of geopolitical developments for the company concerned.

The latter is likely to fall into two categories: company-specific actionable advice to deal with an increasingly unpredictable multi-polar world; and close strategic support on matters, ranging from consideration of new markets and  supply chain diversification to overhauls of company offerings. In a sense, we could see the analyst becoming clients’ trusted advisors.

As AI models can now take on some of the more monotonous and time-consuming tasks required of analysts, those analysts are freer to perform increasingly needed person-to-person interaction with clients.

During the post-Cold War globalisation era of the 1990s, analysts came into their own as companies sought to navigate the new unfamiliar geopolitical landscape. Initially, analytical assessment would have been high-level, looking primarily at inter-state relations. It was communicated to key decision-makers in written formats, with limited face-to-face discussion of its implications. 

The relationship was to become even more distant. With continued multinational expansion around the world, demands on analysts have grown. The scope of work has widened to include the interrogation of new risks, such as climate change, technology and terrorist threats. It has left even less time for client interaction. Now, though, generative AI is freeing up analysts to provide greater value to C-Suites through direct engagement. It could not be more timely, as multinationals increasingly require on-demand, nuanced counsel to help them address unprecedented challenges in their regions of operation, from supply chain disruption, threats against staff to digital sabotage.   

Multi-polarity and the growing threat posed by non-state actors are fuelling volatility, which, in turn, is resulting in an increasingly unpredictable geopolitical environment. Multinationals have never been so vulnerable. Analysis of near- and medium-term threats remains a priority for boards, but they also need to deal more effectively with immediate, unanticipated events, such as cybercrime, severe climate events, military coups and terrorist acts.  

Simultaneously, the political, security and economic tensions that have both driven and arisen from deglobalisation are also prompting multinationals to expedite strategic decisions. With so many emerging and frontier markets looking unstable, boards are having to review their presence in some and downsize in others to mitigate risks. The US/China trade war has long been the catalyst for supply chain diversification. And with Donald Trump’s return to the White House, nearshoring and reshoring will be given even more serious consideration to minimise exposure to the flurry of new tariffs set to further frustrate international commerce.  

With so many potential and actual curbs on global business, C-suites may even start considering reviewing company offerings, switching to product lines less likely to be exposed to trading constraints. All of which benefits from the direct input of analysts, through the provision of analysis that helps clients assess the viability of strategic plans or  by acting as sounding boards for blue-sky thinking.  

Whether advising on immediate or longer-term threats, AI provides analysts the time to better understand the more complex risk environment by filling in knowledge gaps. In practice, this means being able to consult with specialists in their own organisations or those in thinks tanks and institutions around the world who have, for instance, expert knowledge in transnational issues such as cybercrime, extreme climate hazards and international terrorism. Such cooperation, or teamwork, is increasingly key to ensuring tailored analysis is informed by  the whole gamut of threats facing an organisation. 

Without AI, analysts might not have the capacity nor bandwidth to keep up with the growing demand for tailored, client-specific advice.

As well as teamwork, direct client engagement necessitates analysts having, or developing, good communication and interpersonal skills as well as an operational understanding of the companies they are advising. Or, at the very least, their sectors. In times of crisis, they will need to communicate empathetically with under-pressure, stressed executives and be able to tailor their threat assessments, so as to optimise their actionability and general practical value. Put simply, not only understanding the issues at play but also the difficulties executives are facing, in particular the responsibilities they carry. These are significant skill-set additions to the subject matter expertise, broad geopolitical awareness and report-writing competences traditionally required of an analyst. 

Analysts will also clearly have to manage these new one-to-one relationships as there is a risk of them being overwhelmed by engagement requests and demands for overly granular advice – unintentionally and wrongly raising expectations around its utility. Undoubtedly, the more engagement they have with decision-makers, the better they will understand their business and, in turn, the more efficient and effective their input will be. In this respect, embedded analysts are at a distinct advantage as they are already very familiar with the modus operandi of and challenges facing the company they work for.  

While some may have seen generative AI as sounding the death knell for human analysis, it seems that quite the opposite is true. Indeed, it looks to be giving analysts a new lease of life, in doing so adding significant value to their role. Without AI, analysts might not have the capacity nor bandwidth to keep up with the growing demand for tailored, client-specific advice. With it, they do – precisely at a time when such counsel is assuming ever-greater importance.

About the Authors

Giles Alston is Oxford Analytica’s Deputy Director & Senior Analyst for North America, Australasia and Space.

Tatia Bolkvadze is Oxford Analytica’s Cybersecurity and Technology Analyst.