With generative AI now a dominant topic in financial services, private equity leaders often regard the new technology’s potential with a mix of excitement and caution.
Private equity firms are enticed by the new technology’s promise of transformation in operations and innovation. However, in the heavily risk-aware business of acquisition, management, and monetization of private companies, leaders are also keenly interested in use cases and user experiences that demonstrate value in both the near-term and long-term.
Helping these companies to navigate effective strategies to adopt generative AI and modern cloud solutions is our primary focus and a tenet of our work with Microsoft Cloud for Financial Services. Private equity leaders recognize that business transformation also means disruption, which is why solid evidence of the near-term value and impact of generative AI is an important key to success.
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The impact of AI in private equity transformation
Generative AI can transform the way private equity firms do business in a variety of ways. Here are just three areas in which it offers significant potential gains in return on investment (ROI):
- Due diligence accelerated. Generative AI can help accelerate the process of investing in assets by automating and improving various aspects of the investigation and evaluation process. It can streamline information gathering from financial statements, identify trends in financial documents and reports, and analyze contracts, legal documents, and compliance records.
- Generative AI use case: By parsing financial statements, legal documents, and industry reports, a copilot identifies hidden risks and anomalies related to a potential investment opportunity with the goal of avoiding costly mistakes.
- Deal sourcing (origination) efficiency. Generative AI can help firms better identify and evaluate potential investment opportunities in ways that increase speed and create competitive advantages. It can retrieve, summarize, and extract insights from multiple unstructured data sources, automate the generation of documents like requests for proposals (RFPs) and contracts, and automate processes.
- Generative AI use case: By quickly analyzing vast sets of data and documents, a copilot identifies potential investment targets faster and more accurately than before, resulting in a broader deal pipeline and better odds of finding lucrative opportunities.
- Portfolio optimization. Generative AI can help enhance operational efficiency and decision-making related to maximizing the performance and value of a portfolio of investments. It can aid in asset allocation decisions through fast insights, improve efficiency by automating key processes, and improve information sharing by making institutional knowledge instantly available. For example, scenario analysis can help assess the impact of different market conditions on a portfolio.
- Generative AI use case: A firm can analyze and prioritize investments based on potential returns and strategic fit.
An easy first step in AI innovation: Copilot for Microsoft 365
The scope of possibilities in deploying generative AI in private equity is so broad as to sometimes feel overwhelming.
Many firms are initiating long-term innovation with the goal of building customized AI services and products for both internal and customer-facing purposes. For example, Moody’s is now focused on developing generative AI-powered data, analytics, research, collaboration, and risk solutions for financial services, as part of a strategic partnership with Microsoft.
This level of innovation includes developing customized generative AI applications—chatbots and plugins, for example—built on a rich cloud platform for enterprise such as Microsoft Fabric and Azure AI Studio that enable the development and deployment of responsible AI solutions.
Powerful as they are, these innovations require time and planning. In the meantime, many companies also want solutions that can be put to work right away to deliver immediate benefits. This is why Microsoft Copilot for Microsoft 365 is so compelling for many financial services organizations. Designed as a real-time, intelligent assistant integrated deeply into the Microsoft 365 applications that most employees use on a regular basis, Copilot for Microsoft 365 promises to deliver the new value in the near term.
A brilliant digital assistant, or “AI-powered search engine”?
For companies now successfully deploying Copilot for Microsoft 365, the results are impressive. Microsoft research indicates that a company’s productivity and efficiency can be dramatically improved. For example, 70% of people using Copilot reported being more productive and 77% said that once they got up to speed with it, they didn’t want to give it up.1
The key to such success is getting up to speed—or, more precisely, understanding how to begin using Copilot.
When fully deployed in an enterprise environment, Copilot appears in many places across applications and even within documents, as a small icon integrated into a toolbar or workspace. Click it, and a window opens inviting you to engage—and away you go.
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However, one bit of feedback we often hear is that users have only vague ideas of what Copilot can actually do. Lacking guidance and drawing on known paradigms, people often tend to use it like a search engine—in other words, they ask for information based on keywords. Copilot is adept at that, but only as an entry into the real power of AI. Copilot knows and understands huge swaths of data across the enterprise, and draws on it to conduct analysis, perform research, provide insights, explain things, and create entirely new artifacts.
To get such benefits, it is important to understand how to query the technology—in other words, to do what we call “prompt engineering.”
The key to unlocking value: A great prompt
The effectiveness of any natural language-based interaction with a generative AI application depends largely on the quality and specificity of the prompt you submit to it. A well-crafted prompt is essential to generating useful results. A prompt can be a question, a statement, a set of keywords, or even a more complex set of instructions.
This is where a quick demonstration can highlight the true power of Copilot. Try it for yourself. If your company has licensed and enabled Copilot for Microsoft 365 across the business, click the Copilot icon on your browser (be sure to toggle it to Work mode) or on Copilot for Microsoft Teams, and cut-and-paste the following prompt:
- “Summarize my emails, Teams messages, and channel messages from the last workday and today. List action items in a dedicated column. Suggest follow-ups if possible in a dedicated column. The table should look like this: Type (Mail/Teams /Channel) | Topic | Summarization | Action Item | Follow Up. If I have been directly mentioned, make the font of the topic bold.”
In a few moments, Copilot will generate a table that looks like this:
| Type | Topic | Summarization | Action Item | Follow Up |
| Contoso deal report needs updating | Chris will provide missing data. Mark and Shauna need to know when he is finished to update CRM. | Chris needs to be done by the end of the week. | Chris to update Mark and Shauna when he is done. | |
| Teams | Contoso – Internal Sales Enablement call | Updated Dynamics 365 engagement with Contoso on future sales engagement in Canada. | Continue sales engagement with Contoso. | Schedule Contoso meeting. |
| Channel | Contoso meeting 8/11 | Reviewed with Contoso action plan. | Review the meeting recording. | Share any relevant insights or action items with the team. |
For more fun, experiment with prompts like these:
- “Summarize where I was mentioned in email, Teams messages, and channel messages in the last 24 hours. Use that information to prioritize my top three action items for today.”
- “Summarize my emails, Teams messages, and channel messages for the last six weeks about the
. List action items in a dedicated column.”
This exercise, while enlightening, is just the tip of the iceberg in what Copilot can deliver. Functionally speaking, adding Copilot to private equity operations can assist a team with tasks such as researching, monitoring, structuring, supporting processes, and making informed recommendations.
Once a company’s users are fully empowered on prompt engineering, the door is open to realizing greater value in the investments the firm makes with generative AI.
Learn more and move forward
Every AI journey is unique, and the best way to start is to engage with Microsoft or a global partner to explore options and opportunities. To learn more about how Microsoft can help financial services organizations unlock business value and deepen client relationships, see the Microsoft Cloud for Financial Services website. To get started with Copilot for Microsoft 365, contact your Microsoft support team or technology partner.
1What Can Copilot’s Earliest Users Teach Us About Generative AI at Work?, Microsoft, November 2023.
Karen Del Vescovo is the Corporate Vice President for US Financial Services, leading Microsoft’s engagement with US Banking, Capital Markets, Insurance, and other financial services customers and partners. Her focus is to help customers achieve outstanding business outcomes through digital transformation and AI and cloud technology.
As General Manager of US Capital Markets for Microsoft, Paul Miranda leads integrated teams delivering exceptional results that empower US capital markets companies to create and deliver innovative solutions. Based in New York, he focuses on ensuring long-term results for some of the world’s largest firms.