Enhancing Institutional Knowledge with Generative AI

Often, conducting investment research can be akin to mining for a nugget of gold—sifting through mountains of endless data with no guarantee of finding the precise insight you need. Under tight deadlines to deliver a pitch or recommendation, critical insights never have the opportunity to surface, potentially jeopardizing an important deal or allocation.

Institutional knowledge, like an intricate library, requires innovative tools to enhance discovery and uncover the hidden gems within its vast repository. The advent of generative AI (genAI) has transformed the way firms think about bridging this information gap within their enterprise.

According to a recent survey of executives, genAI is already making a considerable impact across their organizations. 83% believe that genAI investments will increase over the next three years, with positive ROI expected in that timeframe. 71% indicated that genAI is enabling their firms to leverage data in decision-making.

Implementing the right search and discovery tools ensures valuable information is brought to light, drives actionable insights, and ultimately informs smart investment decisions.

Below, we outline best practices to optimize search, discovery, and sharing methodologies with generative AI. Platforms like AlphaSense deliver best-in-class solutions for investment firms to streamline and capitalize on their intellectual property, enhance their broader institutional knowledge, and position themselves competitively. 

Understanding Knowledge Management 

Knowledge management is the process by which firms transform information and data they have amassed into actionable insights. Leveraging this proprietary intelligence is crucial for meaningful outcomes, and for remaining competitive in the marketplace. 

For investment firms, proprietary intelligence can include investment theses, pitch decks, memos, meeting notes, and research findings. Frequently, these get siloed away across multiple systems—including data warehouses, pipeline management systems, local drives, legacy systems, email inboxes, and team folders. 

While many firms have already implemented knowledge management systems (KMS), these systems also miss the mark and information overload persists. Content and data remain unorganized, lost in layers upon layers of hierarchy, and are difficult to access. Knowledge management, inclusive of sharing, search, discovery, is not a new problem for firms. The amount of content and data that firms are producing or procuring is only increasing. 

When information sits dormant across many systems, it loses its inherent value. Intellectual property is only as good as a firm’s ability to keep it surfaced and actionable. Otherwise, teams set out to replicate the exact insights they unknowingly already have—wasting resources and time and losing their competitive edge. 

The costs of inefficient knowledge sharing are substantial. Studies show that major U.S. firms suffer annual losses exceeding $40 million as a result of everyday operational inefficiencies due to inadequate knowledge sharing. Solving knowledge management challenges is crucial for a firm’s bottom line as well as its competitive advantage.

Knowledge Retrieval Methodology

Following genAI’s breakthrough year, many firms are experimenting with different tools and approaches, ranging from search, summarization, chat, and content generation. In many cases, the consistent obstacle they face is that the chat and content generation are not delivering on expectations—there are hallucinations, bugs, lackluster responses, or even security challenges. 

Increasingly, enterprise leaders who adopt genAI tools are prioritizing that RAG, or retrieval-augmented generation, is integrated into their solutions. RAG grounds a large language model (LLM)—a type of AI program that can recognize and generate text, among other capabilities—in authoritative content by asking it only to reason over information retrieved from a specified set of data, rather than reproduce knowledge from its training dataset.

RAG methodology enables LLMs to improve accuracy and transparency in terms of how a model is sourcing answers. RAG brings in contextualized data beyond what it was originally trained on, so it can proactively retrieve a more recent earnings transcript instead of an outdated one, or find snippets in a newly published equity research report. 

AlphaSense’s purpose-built approach to RAG is designed specifically for day-to-day tasks and ensures the LLM understands the context of the answers it gives. It assists investment teams with everything from earnings analysis, competitive landscaping, SWOT analysis, and more. 

Additionally, we leverage our existing AI search capabilities—including Smart Synonyms™—to ensure that the platform is pulling the most relevant passages to answer a given query. This creates the dataset that our LLM reasons over in order to best answer your question or summarize a predefined set of values.

Knowledge Discovery Challenges

Centralization 

Often, investment teams spend countless hours searching across disparate data sources, yielding limited, low-impact findings. Traditional market intelligence solutions are reactive by design, leaving companies at risk of falling behind their competitors. Siloed workflows and information inaccessibility translates to missed insights and lack of awareness about emerging trends. The result: a missed lucrative investment, or being unprepared for a critical market event.

Centralizing data and insights is critical to streamline and surface intelligence that can otherwise fall between the cracks.

Search

The volume and depth of data available today presents a high risk for information overload. Firms procure and obtain copious amounts of data, making it difficult to sort through and discover any valuable components.

Researchers browse multiple platforms and systems with limited search technology—such as email inboxes, file storage applications, shared drives, and meeting notes—only to locate a document and then review it in its entirety to assess its value. Platforms like AlphaSense can streamline the process by which information is located and extracted, exponentially increasing productivity potential for your team while reducing costs and saving time. 

Summarization

Investment teams are no strangers to digesting 100-page documents, long industry research briefs, constantly updated models, scattered meeting notes, and data rooms with dozens of lengthy, dense documents. With no good way to summarize key points at scale, it can take endless hours to read through and surface relevant information from one earnings transcript or CIM, let alone multiple.

AI-driven market intelligence platforms sort through vast amounts of data in seconds and zero in on the most relevant datapoints, so you can be confident that you’ll never miss an important insight. AlphaSense’s genAI retrieves and summarizes valuable internal information so that both new and tenured staff spend less time searching for answers to critical questions (e.g. which slide deck did we use for a large-cap tech client presentation?).

Turnover and Onboarding

When an employee leaves an organization, there is a 37% chance the company loses institutional knowledge or IP. This is especially true in the case of an abrupt departure, where the former employee’s work gets buried in folders and storage platforms that are only accessible by them. 

Institutional knowledge lost with employee departure includes crucial notes, expert calls, models and analysis, and memos/write-ups that end up scattered across domains and become impossible to find. Meanwhile, new employees miss out on siloed IP and run the risk of duplicating previous research done on a company or industry, or historical knowledge and positioning on a deal.

Information Sharing 

Findings show that employees spend two hours a week waiting on information from colleagues.

Memos, alerts, and analyses with critical points of information that are shared through archaic methods, like emails, require investors to search subject lines and Excel sheets to obtain the pertinent information they need. 

Given its high-stakes nature and time sensitivity, investment research is most impactful when leveraged in a searchable, efficient way. A centralized hub for knowledge sharing eliminates information silos and the delay in accessing crucial investment intelligence.

Tackling Knowledge Challenges with Best-in-Class Solutions

As investment managers seek out best practices to streamline their enterprise’s knowledge discovery, an industry-leading generative AI tool is central to this endeavor.

Aligning with the right set of generative AI tools is essential to ensure accurate, relevant, and secure intelligence across an organization. This includes features such as— a high quality, trustworthy content universe, transparent citations and verifiable references, and enterprise-grade data protection capable of delivering the insights managers need, and in seconds.

One of these tools is AlphaSense’s Enterprise Intelligence offering, purpose-built with AI search and summarization capabilities to surface insights across internal and external research, so you can centralize siloed research workflows and make investment decisions with less reputational risk. 

Enhance knowledge discovery with secure searches, summaries, and interrogation across your proprietary internal data and a vast repository of 300M+ premium external documents—all powered by our industry-leading AI technology for the most comprehensive investment research. 

Our genAI-powered platform helps you search, discover, and interrogate both your internal research and external content for accurate, verifiable summarizations and answers questions like, “how has our thesis on a company changed,” or “what are the takeaways from my colleagues’ recent management meetings.” 

Level Up your Firm’s Institutional Knowledge

For more than a decade, AlphaSense has pioneered end-to-end solutions that solve the knowledge sharing challenges plaguing many investment organizations.

Our platform is designed to help users find insights faster. In order to do that, we offer a number of tools that extend beyond knowledge discovery features to help users accelerate research tasks:  

• Customizable Dashboards create a centralized information hub for monitoring key companies and themes, while real-time alerts provide instant updates on themes, companies, or industries you are interested in.
• Powerful collaboration tools like Notebook+ and commenting features help teams manage and share insights more effectively.
• Table Tools allow you to streamline your quantitative analysis by enabling you to export modeled time-series data on company financials.
• Image Search allows you to discover insights buried in charts to quickly capture data without reading through pages of documents.
• Snippet Explorer allows you to effortlessly look at any topic or theme and all its historical mentions in a single view.
• Automated Monitoring allows you to set up real-time alerts that send instant updates on any relevant market movements, news, emerging trends, and competitor activities. We also generate snapshots of companies and topics regularly that keep you ahead of the curve with actionable insights.

Unlike most market intelligence platforms, AlphaSense aggregates aftermarket research within our Wall Street Insights® collection. Wall Street Insights® provides access to 1,500+ broker sources for the most relevant, differentiated insights.

Additionally, our expert transcript library features over 45,000 expert transcripts with proprietary insights from former executives, customers, competitors, and channel participants across a range of industries. Premium insights on thousands of public and private companies can drive confident investment decisions and surface business development opportunities.

AlphaSense’s knowledge discovery features help investment firms to defy doubt and overcome information challenges with best-in-class solutions. Discover how AlphaSense outperforms other knowledge discovery solutions for yourself—try Enterprise Intelligence today.