Traditional data processing is reaching its limits. In 2025, data creation will reach 175 zettabytes¹ worldwide, with vast majority taking the form of unstructured information such as documents, video, audio and social media content. As data volumes grow, so does the pressure to turn that information into actionable intelligence.

For information services companies, the explosion of data poses a threat to their competitive edge. Slow manual research, high management costs, fragmented sources and long refresh cycles make it difficult to extract meaningful insights. To stay ahead, they need systems that can extract, contextualize and distill intelligence from data with precision, agility and efficiency.

Businesses are racing to generate real-time insights that enhance customer experiences and deliver continuous value in a volatile and hypercompetitive environment. The challenge is compounded by rising regulatory scrutiny over Environment, Social and Governance (ESG) disclosures, Anti-Money Laundering (AML) reporting and other compliance mandates. These intersect with hurdles like inconsistent formats, multiple languages and widely varying reporting standards across regions.

In response, many businesses are increasingly blending advanced platforms powered by cloud, analytics and AI into workflows to accelerate time-to-insight and improve accuracy and auditability in high-volume environments, processing vast amounts of information into actionable business value.

Next-gen Platforms Are Key to Powering Data Intelligence

Generative AI (Gen AI) combined with hyperautomation is transforming how organizations manage and extract value from data. Next-gen platforms go beyond simple data collection, enabling intelligent research, contextual analysis, automated summarization and publishing across a wide range of sources.

By unifying structured and unstructured data and applying domain-specific context, they turn raw information into harmonized datasets ready for analysis. Proprietary algorithms and AI-driven automation ensure insights are accurate, actionable and delivered at scale, supporting faster, smarter decision-making. Key highlights include:

How Data-intensive Sectors Are Unlocking Measurable Value

For research and compliance-intensive businesses, such as banking and financial services, consulting and research, legal intelligence, market intelligence and data aggregation, implementing next-gen platforms is already driving striking results.

Real-world Impact from WNS

Compliant Business Presentation Design

A top management consulting firm needed advanced support in designing and editing complex presentations without overloading consultants. Traditionally, their consultants struggled with interpreting information hierarchies, building graphics and ensuring strict brand compliance. Deploying AI-driven design intelligence helped automate slide formatting, compliance checks and access to a library of ready-to-use templates.

The result: streamlined workflows, 100 percent quality audit, faster turnaround and uncompromised protection of brand integrity and information security standards such as the EU’s General Data Protection Regulation (GDPR).

Accelerated Cross-Industry Research

One of the largest credit agencies in the US faced challenges in scaling research across industries, including infrastructure, mining, pharmaceuticals, and manufacturing. Manual sourcing and validation of information slowed cycles, raised credibility concerns, and introduced human bias. Leveraging Large Language Models (LLM) and enabling cognitive extraction on a unified platform, the firm automated the sourcing, extracting, processing and updating of industry-relevant information.

This ensured 1.5x faster data refresh cycles, 70 percent higher productivity and a substantial increase in both the breadth and depth of research coverage for more reliable insights – freeing analysts to focus on high-value operations.

Rapid Scaling of Legal Data Intelligence

In the legal sector, a leading US-based legal publisher struggled with slow, costly manual processes for collecting and updating court data. These inefficiencies hindered refresh cycles, increased operational costs and limited scalability.

By implementing a Gen AI-powered cognitive extraction solution with Application Programming Interface (API)-driven updates, the firm reduced refresh cycles from 6 months to 24 hours for thousands of data points. Furthermore, data extraction operations became near touchless after the initial configuration.

Maximizing Investments: A 5-step Approach

For businesses looking to harness the power of AI, the key is to move beyond piecemeal, reactive initiatives and point solutions. Engaging with strategic partners that combine AI-driven capabilities with deep domain expertise and take an enterprise-wide holistic approach, can dramatically improve outcomes and ROI.

Josh Gazes, SVP – Operations at ALM Media shares how a successful strategic partnership enabled their decades-long shift to a digital-first business.

Adopting a structured approach accelerates adoption and optimizes ROI:

Turning Data Complexity into a Growth Catalyst

Businesses are increasingly leveraging Gen AI and LLMs to turn data into actionable intelligence. McKinsey estimates that the strategic use of data analytics and AI could unlock as much as USD 5 Trillion2 in value globally over the next decade. By integrating text, audio, video and image data into a unified intelligence layer, AI supercharges data, providing context-aware insights, detecting emerging trends and surfacing risks before they materialize. This advanced capability allows organizations to recalibrate risk models, monitor compliance and extract deeper customer intelligence – transforming raw data into a driver of competitive differentiation and growth.

References

1. https://www.networkworld.com/article/966746/idc-expect-175-zettabytes-of-data-worldwide-by-2025.html

2. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/upgrading-software-business-models-to-thrive-in-the-ai-era