Transforming data overload into strategic insight

While the age of big data saw firms invest heavily in data analysis, to anticipate market and customer trends, processing the information for useful insights proved like looking for a needle in a haystack. Evalueserve experts Pratyush Prabhat and Alexandru Onojescu explain how AI agents could revolutionise market and competitive intelligence.

We often hear a saying from our clients: "We are drowning in data but starving for insights." Organisations worldwide have access to vast amounts of data yet struggle to derive meaningful and actionable insights from it. This paradox applies to most corporate functions, such as HR, Procurement, Supply Chain, Operations, and Sales, but is especially true for the Market and Competitive Intelligence (MICI) function. MICI spans departments and addresses a broad range of business questions across marketing, sales, product development, pricing, and thought leadership.   

Over the last couple of years, we've seen a continuous transformation of the MICI function across different aspects, all of which are inadvertently linked to the development of AI technologies.   

AI agents: from always-on to spot-on intelligence.   

Technology has enabled the MICI function long before the advent of Generative AI.  At Evalueserve, we have been deploying AI solutions to:   

• Monitor competitors across thousands of sources in real-time, through an always-on approach  

• Turn raw information into clear, digestible insights through briefs, charts, and newsletters  

• Help stakeholders identify relevant information faster with AI-powered search  

• Combine AI automation with human expertise for deeper, contextual analysis.   

Recent GenAI breakthroughs have taken this further. The introduction of Research Bot, our digital assistant on Insightsfirst, enabled us to provide stakeholders with the ability to engage with information and receive instant answers tailored to their needs and interests.   

However, this approach was static. Even with access to comprehensive data, stakeholders (or Evalueserve analysts) still had to piece together information and create reports and presentations manually. At this point, agents represent the next breakthrough, further transforming how MICI professionals and business stakeholders interact with intelligence.   

So, what are AI Agents? The shortest and most precise definition is artificial intelligence systems that can perceive, reason, and take action to accomplish specific goals.   

Why are they a game-changer for MICI? Because they provide speed and scale to workflows that typically require intensive human effort:  

• Once deployed, they automate complex tasks with minimal human intervention.   

• They instantly process massive datasets – both structured and unstructured – through direct API connections.  

• They free analysts and consultants to focus on high-value strategy and interpretation.   

• Most importantly, they create tailored outputs for specific audiences, such as automatically generating pitchbooks, executive bios, competitive battlecards, and white space analyses while identifying key trends and themes.   

At Evalueserve, we have integrated AI Agents within our InsightsFirst platform by leveraging a clearly defined agentic workflow. The process involves a Master AI Agent that receives the command/prompt from the stakeholders and then communicates with several sub-agents to deliver the final output:  

1. A Data Scraper Agent will collect the relevant information from designated sources.  
2. A Data Classifier Agent will tag, sort, and organise the information, and finally,   
3. The Insight Agent will provide the final output in a digestible, ready-to-use format.   

By leveraging AI Agents on top of existing AI functionalities, we are moving toward spot-on intelligence, creating precise market intelligence outputs in minutes instead of days, dramatically improving efficiency, and getting critical insights to decision-makers when needed.   

This transformation brings two fundamental shifts, reshaping how organisations approach market and competitive intelligence.   

Unified intelligence  

The first significant shift enables seamless integration between internal and external intelligence. Previously, MICI specialists and business stakeholders spent countless days or weeks trying to connect the dots (manually triangulating and cross-validating insights from external market data against internal company information). Now, enterprise-level AI adoption enables this convergence to occur automatically, bringing together external market signals, such as news, databases, and expert research with proprietary data, including CRM records, customer feedback, and field team insights, which were previously siloed or scattered across various platforms (Slack, Teams, SharePoint, Box).   

For example, salespeople now receive account-specific battlecards tailored to their individual customers' industry, size, and buying patterns, rather than generic competitor profiles that may not apply. Similarly, when external warning signals, such as a competitor's new product feature, are automatically cross-referenced with internal renewal dates, product and sales teams can immediately identify at-risk accounts and prioritise their response strategies.   

This convergence creates a unified intelligence model that provides companies with a comprehensive view of their business environment. Organisations that embrace this shift can respond faster to changing customer needs and competitive threats, turning intelligence into immediate action.   

Self-service intelligence  

The second major shift is the rise of self-service intelligence capabilities. MICI is evolving from a traditional service-based model, where analysts create and deliver reports, to a product-based platform embedded directly in enterprise technology stacks. This transformation is powered by AI agents and self-service analytics that put intelligence at users' fingertips. This shift has three defining characteristics:  

1. First, democratisation. "Intelligence as a Service" breaks down organisational silos by embedding MICI directly into enterprise systems. Stakeholders across functions—product teams, sales reps, account managers—can access and analyse intelligence independently, eliminating traditional bottlenecks where teams wait days or weeks for specialist reports.  
2. Second, personalisation. MICI platforms become executive co-pilots, delivering insights tailored to each stakeholder's role and responsibilities. AI handles the heavy lifting—curating, analysing, and synthesising data—while automatically adapting outputs to match individual functions and decision-making needs.  
3. Third, integration. Organisations are moving beyond AI "point solutions"—single-purpose tools operating in isolation—toward integrated intelligence that connects data, insights, and actions across the enterprise. For MICI, this enables real-time, coordinated responses where competitive intelligence immediately triggers aligned actions across sales, product, and strategy teams.  

In conclusion, AI and AI agents are transforming MICI from a reactive, manual process into a proactive, real-time, and predictive strategic asset, enabling organisations to anticipate market shifts, outmanoeuvre competitors, and make faster, more informed decisions than ever before.  

Evalueserve has over 20 years of experience as a partner for the world's largest professional services firms, financial institutions, and corporate enterprises. With a network of 5000 subject matter experts, the firm uses AI technologies to convert raw data into actionable insights that empower strategic decisions.