Agentic AI is changing how consulting firms operate, the autonomous agents are streamlining research, surfacing insights, and generating deliverables in record time.
Across the industry, these systems are being applied to onboarding, risk monitoring, pitch development, client personalization, and more. As agentic AI becomes embedded in daily workflows, it is also raising new expectations around data quality, workforce training, and responsible implementation.
Read on to explore how these shifts are playing out across the consulting sector, using insights drawn from The Agentic AI Tech Stack: A Consultant’s Guide to Smarter, Faster Decision-Making, a new ebook that uncovers how consulting firms are integrating agentic systems, what’s working in practice, and what it takes to scale the technology responsibly.
What Agentic AI Really Means
Some still associate AI in consulting with chatbots or basic automations. However, agentic AI is quite different. Imagine an intelligent system where software operates independently to complete tasks and achieve goals on behalf of users—that’s what agentic AI is. Unlike a chatbot, which typically responds to direct prompts, agentic systems can take meaningful action without constant human input, often coordinating multi-step workflows made up of individual agents working together to solve more complex challenges. Jim Olsen, CTO at ModelOp, explains it best: “Each [agent] of the team brings both abilities, or tools, and expertise, or training to an overall task, while agentic AI is the whole team working together to solve the problem.”
This level of autonomy changes what consultants can do, and how quickly they can do it, whether that’s in support of their firm’s operations, or a client’s.
Where Agentic AI Adds Strategic Value
Consultants are leveraging agentic AI in ways that go far beyond research automation—though that remains a top priority, with 58% of executives naming research and summarization as their leading use case. These systems are delivering value across several key areas:
- Risk monitoring: Agents screen media and legal data in real time to flag reputational, regulatory, and financial risks.
- Pitch development: Multi-agent systems draft client briefings, presentations, and proposals based on internal best practices.
- Decision support: AI agents process market data and internal insights to help consultants act quickly and confidently.
- Client personalization: Recommendations are tailored based on a client’s past interactions, preferences, and goals.
Organizations using agentic AI report a 35% reduction in decision-making time, a 42% improvement in resource allocation efficiency, and a 28% boost in employee satisfaction by minimizing routine tasks. These technologies improve speed and elevate the strategic role of consultants by freeing them to focus on higher value thinking and execution.
Why the Tech Stack Behind Agentic AI Matters
Agentic AI only performs as well as the system supporting it. For consulting firms, that means creating a framework which allows agents to access trusted data, make informed decisions, and deliver timely outputs. Before you can think about delivering automated insights to tools consultants already use (like Slack, email, dashboards, or internal platforms), several other layers must first be put in place. A complete agentic tech stack includes:
- A data layer that feeds in internal and external information
- A reasoning layer powered by large language models or task-specific tools
- A memory layer to retain context and learn over time
- An orchestration layer to coordinate multiple agents and workflows
- An output layer that delivers results to Slack, email, dashboards, or reports
Each layer plays a critical role. Without high-quality data, agents struggle to produce accurate or relevant results. Without orchestration, agents work in isolation instead of delivering coordinated value. And without memory, systems can’t learn user preferences and personalize outputs over time.
Receiving an inaccurate or unreliable output is flagged by one in three consultants as being a key concern—in many cases, that risk traces back to poor data infrastructure or disconnected tools. Getting the stack right is a must, as it’s what enables consultants to trust and scale the AI systems that are becoming embedded in everyday work.
Why Some Firms Struggle
Agentic AI offers clear advantages, however, not every rollout succeeds, or delivers the results firms expect. In fact, Gartner predicts nearly a third of generative AI projects will be abandoned by the end of 2025. The cost of failure is high: not just in wasted investment, but in reputational risk, staff resistance, and lost client trust.
Below are five critical blockers which consistently derail implementation efforts, and must be avoided:
- Poor data undermining quality of agentic outputs
- Siloed systems that restrict agent access to relevant tools or content
- Lack of internal expertise to build, govern or even properly evaluate agentic workflows
- Regulatory complexity that creates hesitation or legal exposure
- Failure to communicate clearly with staff and clients about how AI is being used
For consulting firms, trust and explainability are everything. Without responsible implementation, even the most advanced agent can damage client relationships. That’s why 54% of consultants surveyed in the LexisNexis Future of Work Report reiterated the need for AI systems to be transparent.
What Leading Firms Are Doing Right
The Big Four and MBB are already setting the pace for exploring different use cases for agentic AI in consulting:
- EY has deployed 150 AI agents in its tax division.
- Deloitte’s Zora platform is projected to reduce costs by 25 percent and boost productivity by 40 percent.
- McKinsey’s internal AI chatbot Lilli is used by 80 percent of the firm and saves 30% of the consultants’ time on average.
Boutique firms are also getting ahead by using agentic systems to compete, automating research and business development tasks that would otherwise require far greater headcount. This shows that agentic systems are perhaps no longer something unique or used as a rare feature for competitive edge but are instead becoming an expected part of a firm’s resource pool.
The Skills Shift Is Already Underway
92% of management consultants believe their employees need new capabilities to keep up with AI. In addition to upskilling existing staff, many firms are beginning to explore new roles to support agentic AI adoption including AI trainers, data specialists, and governance experts. A recent Microsoft survey found growing global demand for these roles across 31 countries. Meanwhile, 42% of management consulting firms have already implemented advanced AI training, compared to just 15% across other industries.
“Future consultants will need an engineering-first mindset,” says Deloitte’s Jillian Warner. That doesn’t mean writing code, but it does mean understanding how AI works and how to use it responsibly.
Responsible Use Isn’t Optional
Clients expect transparency.
Staff need reassurance.
Regulators demand compliance.
That’s why successful agentic AI strategies include guardrails from the start such as audit trails, human oversight, and clear communications on how data is being used.
Best practices are starting to crystalize for how to gradually adopt agentic tools. PwC’s executive playbook takes the approach of deploying AI in a “copilot” role, encouraging teams to work alongside agents while trust and accuracy are built over time.
What Comes Next
Agentic AI is not a tool to be tested in isolation. It is reshaping how consulting work gets done across research, strategy, risk, and delivery.
According to a 2025 Microsoft survey, 82% of organizations expect agents to be integrated into their workflows within the next 18 months. For many consulting teams, this shift is prompting a rethink of strategy, delivery models, and client engagement.
Firms that understand this are already building the systems, skills, and safeguards they need to consult with confidence.
To explore how your team can make the most of this opportunity, download the full ebook: The Agentic AI Tech Stack: A Consultant’s Guide to Smarter, Faster Decision-Making