How Deep Research Takes Market Intelligence to the Next Level

Generative AI has been transforming, accelerating, and enhancing market intelligence across industries for several years. With the advent of genAI, the pace of research has increased exponentially, enabling business professionals to incorporate more sources and perspectives into their analysis than was ever humanly possible.

Deep research tools represent the next frontier of generative AI. Moving beyond surface-level content generation and knowledge retrieval, deep research tools harness genAI to perform in-depth analysis, pattern recognition, and synthesis across large, complex datasets — all with cited, verifiable sources. This iteration of genAI unlocks unprecedented depth and breadth in research and represents a quantum leap in knowledge acquisition.

Corporations, financial institutions, and consultancies are quickly discovering the immeasurable value of deep research tools in market intelligence — greater accuracy, richer context, stronger user confidence, and higher ROI. Ultimately, this technology is key to making the most data-driven, strategic decisions and getting a competitive edge in today’s lightning-fast markets.

What is Deep Research?

Deep research, in the context of generative AI, refers to the capability of AI to perform comprehensive, multi-layered analysis across vast and often unstructured information sources. Usually a component of generative AI chatbots, this mode takes generative outputs from quick summaries of existing knowledge to in-depth, well-cited reports. This process simulates the depth, nuance, and context-awareness of a skilled human researcher, but at machine scale and speed — which means the research is significantly more comprehensive, efficient, and in-depth than anything a human could do.

Speed vs Depth in Market Intelligence

Is speed or depth more important when conducting market intelligence? Generative AI is known for its ability to provide almost instantaneous outputs, and one of its key value offerings is its ability to accelerate speed to insight.

Deep research tools, on the other hand, require significantly more time to generate a report. Since the AI is parsing through more sources and performing deeper analysis, it usually takes between 5-30 minutes to deliver an output, depending on the complexity of your query and the volume of data it needs to analyze.

Though it may seem that using deep research tools means sacrificing speed for depth, this is not the case. The kind of analysis these tools are able to complete in under half an hour would take a human analyst days or even weeks of manual effort, with inevitable gaps, missed connections, or errors due to the limits of human time and attention.

By using deep research tools, you’re not sacrificing speed — you’re compressing days of work into minutes, freeing up time to focus on applying insights, shaping strategy, and driving outcomes. This technology can also supercharge workflows across teams: preparing for investor meetings, building client-facing pitch decks, monitoring tangential competitors, producing polished internal reports, and more.

With deep research, you don’t ever have to choose between speed or depth in your market intelligence again — you get both, at a level of precision and comprehensiveness that was previously out of reach.

Deep Research Key Players

While the generative AI market is rapidly expanding — with thousands of players vying for market share — deep research remains a more specialized and emerging capability. Only a select few companies offer true deep research functionality, and these key players include:

AlphaSense

Deep Research in AlphaSense performs thoughtful, iterative research on-demand — doing dozens of searches, parsing through millions of source documents, and producing detailed analysis in the form of company primers, market landscapes, pitch recommendations, and more. AlphaSense’s key differentiation is the breadth and depth of financial and business content that our Deep Research pulls from — exclusive sources like broker reports and expert transcripts, as well as company documents, news, and regulatory documents.

With Deep Research, AlphaSense users can be confident that each output is accurate, reliable, and verifiable with a single click. And because our AI is built to learn from and leverage premium financial and business data — like 200k+ expert call transcripts — users get access to more differentiated and powerful insights, giving them the competitive edge. This feature is available on an unlimited basis for all AlphaSense users.

OpenAI

The makers of ChatGPT were the first to popularize and democratize generative AI chatbots, and they were also one of the first to release a Deep Research mode — enabling deeper, more precise, and more comprehensive research.

While the Deep Research mode enhances the quality of research that can be done with ChatGPT, it’s still pulling from public web data, which means it’s limited in its scope and accuracy. OpenAI’s Deep Research also cannot access paywalled content or databases that restrict AI crawlers, potentially omitting valuable information from its reports. Finally, this mode only allows limited queries, based on users’ subscription tier.

Related Reading: AlphaSense vs ChatGPT

Google Gemini

Google was the first company to release a Deep Research mode, as part of their Gemini generative chat experience. Gemini Deep Research creates detailed, organized reports by autonomously searching and analyzing information from across the web. Key features include multi-step planning, iterative web browsing, and comprehensive reports with clear insights and source links. Gemini Deep Research also integrates with Google Docs, facilitating easy sharing and further editing.

Similarly to OpenAI, Gemini’s Deep Research pulls data from the public web, which means it’s limited in its scope and accuracy, particularly when it comes to financial or business research. Gemini’s Deep Research also only allows limited queries, depending on users’ subscription tiers.

Perplexity

Perplexity’s Deep Research mode is similar to the above-mentioned platforms, except it’s significantly faster, delivering reports in approximately 2-4 minutes. Research findings can be transformed into visually appealing, comprehensive content using Perplexity Pages, facilitating easy sharing and presentation of information.

However, like OpenAI and Gemini, Perplexity’s Deep Research only scours public web data, which limits its usability for financial and business use cases and makes the research more vulnerable to inaccuracies and hallucination. The amount of Deep Research queries users can conduct also depends on the subscription tier — Perplexity limits the number of queries for every tier except Enterprise.

Related Reading: AlphaSense vs Perplexity

AlphaSense’s Deep Research

When it comes to financial and market research, AlphaSense’s Deep Research is unmatched. Like the rest of our AI tools, Deep Research leverages our exclusive collection of 10,000+ private, public, premium, and proprietary data sources to produce its analysis, sources that include:

Company documents for both private and public companies, including earnings transcripts, company presentations, SEC and global filings, ESG reports, and press releases
Broker research from Wall Street’s leading firms, covering global sector themes, industries, and companies from 1,000+ sell-side and independent firms
Expert call transcript library with over 200,000 vetted interviews (including with competitors, suppliers, customers, and KOLs)
News, industry reports, trade journals, and regulatory documents

Additionally, our Enterprise Intelligence customers have the added advantage of being able to upload key internal documents that can then be sourced as part of Deep Research’s analysis — extracting maximal value out of their firm’s internal knowledge.

Deep Research is designed to augment core workflows for our customers, enabling strategy leaders to conduct research, create detailed briefings, and automate large-scale synthesis in minutes — not weeks.

With Deep Research, users can:

Ask for thorough industry primers, acquisition ideas, competitive landscapes, and more
Give the model instructions about the structure and format of the desired output
Set and forget it – let the model work for 5-30 minutes while you focus on other tasks
See a full log of how the tool formed its research plan, reasoned through different topics and sources, and generated its report — step-by-step

AlphaSense’s Deep Research eliminates days of manual work, not to mention the risk of missing critical pieces of information. No matter what industry you are researching or specific use case you are bringing, Deep Research will transform your workflows and give you the competitive edge.

How Clients Are Using AlphaSense’s Deep Research

The following are some of the key use cases for deep research in market intelligence across a variety of industries:

Corporates

Corporates can incorporate Deep Research into the following workflows:

Market Landscaping – Ask Deep Research to summarize any specific market
- Prompt: Summarize the market of pet healthcare providers.
Competitive Intelligence – Ask Deep Research to summarize a specific competitive landscape
- Prompt: Summarize the competitive landscape for buy now, pay later (BNPL) tools. Please include SWOTs for each player, key product announcements, any pricing information, and regionalization strategies.
Strategic Response Planning – Ask Deep Research to generate a comprehensive strategy, given specific parameters
- Prompt: Develop a comprehensive strategy of how we could leverage subsidies for domestic production of critical technologies.
Investor Communication – Use Deep Research to help you prepare for earnings season and answer any investor questions
- Prompt: I am an IR analyst at [Company] preparing for Q1 earnings next month. Analyze risks that could impact investor sentiment and market perception by focusing on AI leadership, valuation, competitive dynamics, and how [Company] is positioned amid current market uncertainty. Use prior quarter earnings Q&A (both ours and peers’) to anticipate the most likely investor questions.

Consulting

Consultants can incorporate Deep Research into the following workflows:

New Business Development – Ask Deep Research to analyze specific industry trends
- Prompt: Analyze digital transformation reprioritization trends as companies focus on projects with clearer ROI
Client Pitch Preparation – Ask Deep Research to create a report on a topic relevant to your client
- Prompt: Develop a report on optimal automation strategies for manufacturing based on recent investment trends
Value-Added Client Deliverables – Ask Deep Research to create a roadmap for your client based on specific parameters
- Prompt: Develop a manufacturing automation roadmap for our client based on successful implementations across industries.

Investment Banking

Investment bankers can incorporate Deep Research into the following workflows:

Deal Impact Analysis – Use Deep Research to understand how external factors may influence deals
- Prompt: Evaluate how enhanced regulatory review processes for cross-border M&A reported by Financial Times affect timeline and completion probability for technology deals.
Client Advisory Services – Use Deep Research to develop client-facing reports
- Prompt: Develop a report around how companies are successfully adapting to the new 100% tariffs on Chinese EVs and battery components.
M&A Prep – Use Deep Research to help you develop winning client pitches
- Prompt: I’m an investment banker. Provide me a list of targets to pitch for [Client Company] to acquire based on management’s strategic priorities.
Industry and Company Research – Use Deep Research to help you conduct in-depth research on specific industries or companies
- Prompt: Create a primer for the geothermal cooling industry.

Private Equity

Private equity analysts can incorporate Deep Research into the following workflows:

Target Due Diligence – Use Deep Research to conduct due diligence on target companies
- Prompt: Evaluate [Company]’s exposure to new price transparency regulations.
Portfolio Company Support – Use Deep Research to help you come up with portfolio company strategies based on current events
- Prompt: Develop alternative supply chain strategies for automotive portfolio companies affected by new tariffs on Chinese EV components.
Opportunistic Acquisitions – Use Deep Research to uncover new opportunities in the face of specific macroeconomic events
- Prompt: Which manufacturing companies are benefiting from reshoring trends accelerated by recent tariffs and trade tensions?

Asset Management / Hedge Funds

Asset managers and hedge fund analysts can incorporate Deep Research into the following workflows:

Portfolio Risk Assessment – Use Deep Research to analyze how your portfolio companies might be impacted by external events
- Prompt: Perform an analysis on how my portfolio companies are exposed to the new export controls on chip manufacturing equipment to China.
Client Communications – Use Deep Research to help you put together client materials.
- Prompt: Write a letter to investors from the perspective of a wealth manager explaining what is happening with the markets as a result of recent Trump tariffs. Please use charts and quantitative data where necessary to help explain to wealth management clients what is happening.

Explore Deep Research Replays

Try Deep Research Today

With AlphaSense’s Deep Research, you can be more competitive in fast-moving markets because you are leveraging insights from the most high-quality and reliable sources. Compress weeks of analysis into minutes with AI workflows that instantly synthesize complex information while maintaining the traceability required for high-stakes decisions. Increase your confidence in your research, knowing you are using AI that was purpose-built for business decisions.

Discover the power of Deep Research for yourself. Start your free trial today.