Published by Intent Amplify, delivering research-driven insights for legal knowledge leaders, AI leaders, risk leaders, architecture teams, legal operations leaders, innovation teams, and professional services decision-makers navigating trusted AI adoption, traceability, governance, regulatory expectations, and digital transformation.
Legal research has always been built on proof, precedent, and source authority. A lawyer can move quickly, write clearly, and advise confidently, but when a client, regulator, court, or internal risk team asks, "Where is that coming from" the answer must point to a trusted, verifiable source.
That is why the next phase of legal AI will not be defined by who can generate the fastest paragraph. It will be defined by who can deliver the most defensible, traceable, and governed answer.
Across professional services, AI adoption has already moved from curiosity to operating reality. Thomson Reuters' professional services research surveyed more than 1,500 professionals across more than two dozen countries, and found that 40% of organizations are now using GenAI, up from 22% the previous year. Among professionals already using GenAI, more than 80% use it at least weekly, and 87% expect GenAI to become central to workflow within the next five years.¹
Agentic AI is moving into the same conversation. Only 15% of professional services organizations currently use agentic AI tools, but another 53% are planning or considering them, while 77% expect agentic AI to become central to workflow by 2030.¹
For law firms, accounting advisors, compliance specialists, and professional services providers, that growth creates a harder question: Can AI be trusted when the answer affects a client's legal position, regulatory exposure, tax treatment, privilege considerations, compliance posture, or board-level decision?
Progress.com's case study on Progress Agentic RAG answers that question through a practical example: a leading European law firm used Progress Agentic RAG to create trusted, traceable AI search experiences for legal and accounting research.
View the Progress Agentic RAG case study
Key Figures at a Glance
Progress reports that its Agentic RAG-as-a-Service approach can deliver up to 95% faster AI-readiness and more than 80% cost savings compared with building similar solutions internally.³
In traditional enterprise search workflows, Progress notes that employees may open 8-12 documents to answer a single question.⁴
In the Progress law firm case study, Agentic RAG supported approximately 300 legal and accounting professionals, helped process thousands of questions per month, and served a firm supporting more than 20,000 private and public clients.²
Professional services organizations still struggle to measure AI value: only 18% collect ROI metrics around AI, while 40% do not know whether their organization tracks AI ROI at all.¹
Legal professionals surveyed by Thomson Reuters expect AI to free up nearly 240 hours per year, up from 200 hours in the prior year, creating an estimated $19,000 in annual value per professional.⁵
In the U.S. legal and tax/accounting sectors, Thomson Reuters estimates AI-related time savings could contribute a combined $32 billion in annual impact. Organizations with visible AI strategies are 2x as likely to experience revenue growth from AI adoption compared with those using more informal or ad hoc approaches.⁵
Microsoft's Work Trend Index analyzed 31,000 workers across 31 countries, LinkedIn labor-market trends, and Microsoft 365 productivity signals; it found that 82% of leaders say this is a pivotal year to rethink strategy and operations, while 81% expect AI agents to be moderately or extensively integrated into their AI strategy in the next 12-18 months.⁶
IBM's AI research found that AI-enabled workflows are expected to expand from 3% in 2024 to 25% by 2026, an 8x increase.IBM also reports that 64% of AI budgets are now spent on core business functions, while ad hoc AI adoption has declined from 19% to 6% year over year.⁷
IBM's Cost of a Data Breach research found the global average breach cost reached $4.88 million, a 10% increase from the previous year, with 70% of the 604 studied organizations reporting moderate or significant operational disruption.⁸
Google Cloud's grounding documentation states that grounding APIs can return a support score from 0 to 1, support up to 200 facts with 10,000 characters each, and provide citations connecting claims to supporting facts.⁹
McKinsey's agentic AI research shows an illustrative performance comparison in which reinvented agent-enabled processes can reduce resolution time by 60-90%, compared with 20-40% for optimized agent-enabled workflows and 5-10% for GenAI-assisted workflows.¹⁰
PwC's AI Jobs Barometer analyzed close to one billion job ads and found that industries most exposed to AI saw 3x higher growth in revenue per employee, with 27% productivity growth compared with 9% in less-exposed industries.¹¹
The Legal Knowledge Benefit: Confidence, Traceability, and Defensibility
Legal clients do not buy technology. They buy confidence.
They want faster answers, yes. But not faster guesses. They want a law firm that can respond quickly while still showing the evidence behind the answer. That is the real value of traceable AI in legal research.
This matters because legal AI risk is no longer just about whether a system can draft a polished paragraph. The real question is whether the professional can inspect the source, validate the retrieval path, assess the reasoning, and decide whether the answer is safe to use in a client, regulatory, or litigation-sensitive setting.
Progress Agentic RAG is positioned around that exact requirement. It does not simply produce an answer. It helps professionals see where the answer came from, verify the source, inspect the retrieval path, and decide whether the output is suitable for professional use.
For a client, that changes the experience. Instead of waiting through a long research cycle or receiving a vague AI-assisted summary, the client benefits from a faster, more transparent advisory workflow. The lawyer remains in control, but the search, retrieval, synthesis, and first-draft burden become lighter.
That is where AI becomes useful without becoming reckless.
Why the Progress Case Study Matters
The law firm in the Progress case study faced a familiar professional services challenge. Its teams needed to answer complex legal and accounting questions in an environment shaped by regulation, confidentiality, and constantly changing rules. Traditional research workflows required lawyers to search through legislation, guidance, internal know-how, and client-specific context before producing an answer.
The firm had explored building its own AI-powered research solution. It also evaluated hyperscalers and other RAG options. The issue was not whether AI could generate text. The issue was whether the firm could trust the answer, verify the source, control retrieval behavior, and demonstrate why a specific legal interpretation had been suggested.
Progress Agentic RAG helped solve that by creating a governed, traceable knowledge architecture. The solution ingests internal legal and accounting knowledge, combines it with curated external sources, and allows the firm to tune retrieval strategies for different legal and regulatory domains.
For legal teams, that distinction is critical. Employment law research does not behave like tax research. Public-sector guidance does not behave like commercial contract review. A one-size-fits-all AI layer can miss the nuance that lawyers spend years learning to recognize.
Progress helped the firm build an AI assistant that respects that complexity.
Client Benefit: Faster Service Without Removing Legal Judgment
The strongest AI experiences in professional services do not remove experts from the loop. They remove the friction around experts.
In this case, the assistant gives lawyers draft answers grounded in the firm's own knowledge and authoritative sources. Lawyers can validate, refine, and finalize the output instead of beginning every query from a blank page. That approach aligns with broader industry trends. Thomson Reuters' Future of Professionals Report 2025 found that professionals expect AI to free up significant portions of time currently spent on research, document review, and information retrieval, while Microsoft's 2025 Work Trend Index reported that knowledge workers increasingly rely on AI to reduce repetitive cognitive tasks and accelerate decision-making. By surfacing trusted answers from governed knowledge repositories, Progress Agentic RAG helps firms convert those efficiency gains into practical client value.
That creates three immediate client-facing advantages. First, response times improve. Clients receive answers sooner because lawyers spend less time searching across multiple repositories and more time reviewing relevant information. Second, consistency improves. A governed knowledge layer reduces the risk that two professionals answer the same question differently because they relied on different documents or incomplete research. Third, the quality of the conversation improves. Progress's law firm deployment emphasizes traceable answers with source citations, enabling lawyers to demonstrate the basis for recommendations rather than relying solely on professional authority. This aligns with industry best practices around grounded AI, where answer traceability is increasingly viewed as essential for trust, compliance, and risk management. For clients, the result is greater confidence that advice is not only fast but verifiable.
Client Benefit: A Governed, Traceable AI Service Experience
The most strategic part of the Progress case study is the client-facing portal.
The firm did not stop at internal productivity. It launched a secure AI legal assistant that selected clients can use to ask routine legal questions and receive grounded answers backed by the firm's expertise. Lawyers still retain final control over legal advice, but clients gain faster access to the firm's knowledge. This reflects a broader shift identified by McKinsey's Seizing the Agentic AI Advantage report, which argues that organizations are moving beyond isolated AI productivity tools toward agentic systems that directly reshape customer experiences and service delivery models. Similarly, IBM's From AI Projects to Profits research found that organizations achieving the greatest returns from AI are increasingly embedding it into customer-facing workflows rather than limiting it to internal operations.
That is bigger than operational efficiency. It is a branded service model. A law firm that can productize trusted knowledge through a secure, traceable AI interface is no longer just selling hours. It is selling access, responsiveness, confidence, and a differentiated digital experience. For clients, routine legal questions no longer have to wait in the same queue as highly complex advisory work. For the firm, it creates a more scalable way to serve demand while strengthening its market identity as a technology-forward, trust-first advisor. The trust dimension is particularly important in an environment where data protection and governance are under scrutiny. IBM's Cost of a Data Breach Report 2025 notes that breach-related costs continue to rise globally, reinforcing the importance of secure architectures and transparent AI systems. By combining grounded retrieval, source traceability, and human oversight, the Progress approach demonstrates how firms can innovate client experiences without compromising the accountability that professional services depend on.
Why Traceability Is Becoming a Legal AI Governance Requirement
There was a time when saying "we use AI" sounded innovative. That window is closing.
Clients are becoming more sophisticated. Many already use AI themselves. They know AI can be useful, but they also know it can be wrong. The future trust signal will not be AI adoption alone. It will be governed, explainable, and traceable AI adoption.
That means firms will need to answer harder questions.
Was the user authorized to retrieve those sources?
Was privileged or restricted content protected?
Was the retrieval path logged and auditable?
Was the answer grounded in approved knowledge sources?
Was the output reviewed before being used in a client-facing context?
Progress Agentic RAG gives firms a way to move toward that model. Its value is not just speed. Its value is the ability to make AI outputs more explainable, auditable, and aligned with professional judgment.
In legal services, that is not a technical nice-to-have. It is quickly becoming a trust requirement.
Why Progress Is Positioned for Legal-Grade AI Trust
Progress has an important branding advantage in this conversation because it is not asking law firms to treat AI as a creative shortcut. It is positioning Agentic RAG as a trusted AI infrastructure for knowledge-heavy, compliance-sensitive organizations.
That message fits the market moment. Professional services firms are under pressure to adopt AI, but they cannot adopt it the way casual users do. They need governance, source control, access permissions, model flexibility, citation visibility, quality metrics, secure deployment, auditability, and the ability to continuously improve the system as laws, documents, regulations, and client needs change.
Progress Agentic RAG is built for that layer of work: turning scattered enterprise knowledge into traceable AI answers that professionals can verify.
For clients, the benefit is not simply "AI-powered legal research." The benefit is a better advisory experience: faster, clearer, more transparent, and easier to trust.
For law firms, the benefit is strategic: stronger client service, reduced manual research burden, differentiated digital offerings, and a more credible path to AI adoption under legal-grade expectations.
The market is not waiting. AI is already changing how clients search for answers, how professionals manage workload, and how firms define value. The firms that win will not be the ones that automate the most blindly. They will be the ones who make AI traceable, governed, secure, and accountable.
Download the full Progress case study PDF to explore how a leading law firm used Agentic RAG to build trusted, traceable AI research experiences with governed retrieval, source validation, and client-facing AI assistance.
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References
- Thomson Reuters (2026) AI in Professional Services Report 2026. Thomson Reuters, 2026.
- Progress (n.d.) Progress Agentic RAG Enables Trusted, Traceable Answers for a Leading Law Firm's AI Search Experiences. Progress Software Corporation.
- Progress (n.d.) RAG-as-a-Service Solution: Progress Agentic RAG. Progress Software Corporation.
- Progress (n.d.) From Search to Answers with Agentic RAG. Progress Software Corporation.
- Thomson Reuters (2025) Future of Professionals Report 2025. Thomson Reuters, 2025.
- Microsoft (2025) 2025 Work Trend Index Annual Report. Microsoft Corporation, 2025.
- IBM (2025). From AI Projects to Profits: How Agentic AI Can Sustain Financial Returns. IBM Corporation, 2025.
- IBM (2025) Surging Data Breach Disruption Drives Costs to Record Highs. IBM Corporation, 2025.
- Google Cloud (n.d.) Check Grounding with RAG. Google Cloud.
- McKinsey & Company (2025) Seizing the Agentic AI Advantage. McKinsey & Company, 2025.
- PwC (2025). PwC 2025 Global AI Jobs Barometer (PwC), 2025.
