By Carolyn Badaracco
“Embrace it.” That’s what most top Georgia business leaders will say when you ask how businesses can best approach AI.
But what does embracing AI look like in real-time?
Principal and aIQ Program Lead Rahsaan Shears with KPMG LLP in Atlanta told Georgia Insider what has worked at the organization, to date, and she made this critical point: AI isn’t just a technology shift, it’s an operating model shift.
KPMG and AI: An intentional partnership
As a Big Four global professional services firm, KPMG provides audit, tax and advisory services to organizations across industries.
Shears describes the company’s AI adoption rate in a way that sounds nimble, intentional and wise.
“KPMG’s AI journey started with a deliberate choice to be our own Client Zero — using AI to transform how we work before advising clients,” she said. “That effort is anchored in our aIQ program, which set up a firmwide, executive-led initiative, not a standalone technology experiment.”
From the beginning, Shears reports that KPMG centralized its leadership and established clear principles, “AI first, bold, fast and responsible,” and put the right governance, funding and measurement in place to scale responsibly.
“We’ve implemented this through a multidisciplinary model that brings together technologists, industry specialists and risk professionals,” she said. “AI is embedded into our core delivery platforms across audit, tax, advisory and internal operations, supported by AI and Data Labs that allow us to move quickly while maintaining strong oversight.”
All of this is governed by the company’s trusted framework to ensure transparency, accountability and human oversight as AI is designed and deployed.
In terms of capability, KPMG’s own spans generative AI, advanced analytics and, increasingly, agent-enabled systems that can “plan and act under human governance,” Shears stated.
Scouting the field — and taking action
According to KPMG’s research and Q1 2026 AI Pulse Survey, 54% of organizations are now actively deploying AI agents — up from 11% in early 2024.
This signals a shift from pilots to enterprise-level execution.
Speaking from her internal vantage, Shears said, “These capabilities are built into platforms like KPMG Workbench, giving us an enterprise-grade AI foundation designed for trust, scale and long-term impact.”
Practically, yet dramatically, AI is improving speed, precision and consistency at KPMG. And again, it’s about embedding AI into the core of the organization’s work.
As Shears put it, “By embedding AI directly into workflows, our professionals can analyze more data, surface insights earlier and spend more time on judgment-driven, strategic work,” such as automating complex research, accelerating compliance and reporting, and strengthening scenario modeling and decision support.
Surprising benefits
According to Shears, one revelatory benefit for KPMG has been the impact on quality and confidence.
“AI has reduced manual rework and variability, which improves consistency across engagements,” she said. “Our teams also report less stress, higher quality output, and more time for meaningful client conversations.”
All of these being benefits matter just as much as efficiency gains. And Shears said KPMG’s experience is consistent with what they’re seeing in the market.
The company’s Q1 2026 AI Pulse Survey also noted that while AI investment continues to accelerate, averaging $207 million per organization over the next 12 months, 65% of leaders say they struggle to scale use cases. And 62% cite workforce skills gaps as the biggest barriers to realizing ROI.
“Another surprise was how quickly trust became a differentiator,” Shears said. “Clients aren’t just asking whether AI is fast, they want to know if it’s governed, explainable and safe.”
She added, “Our early investment in trusted AI and assurance capabilities has positioned us well, especially as AI systems become more autonomous.”
Generative AI in operation
Shears reports that KPMG is using generative AI (a type of AI that can create new content rather than just analyzing or classifying existing data) in practical ways across the firm.
“Internally, it supports drafting, summarization, research and knowledge retrieval, helping our professionals move faster from information to insight,” she said.
In client work, on the other hand, “it’s used to generate first draft analyses, synthesize complex regulatory or contractual information, and support proposal and solution development — always with human review and accountability,” Shears said.
Recently, KPMG has begun to move beyond standalone generative AI tools to agent-enabled workflows. The impact: not just speed but also coordination at scale.
As Shears reports, “The AI Pulse shows that 73% of organizations using AI agents are automating workflows that span multiple functions, helping break down silos and improve consistency across the enterprise.”
AI adoption on a broad — and smart — scale
Across Georgia’s major industries — including manufacturing, financial services, healthcare, logistics and professional services — AI is moving out of experimentation and into core operations.
“Leaders are prioritizing use cases tied to productivity, supply chain resilience, customer experience and risk management,” Shears reported.
It’s an approach that mirrors findings from the 2026 KMPG U.S. CEO Outlook Pulse Survey.
The survey shows CEOs pressing ahead with AI investments while identifying data readiness, governance and trust as the key constraints to scale.
Circling back to the Q1 2026 AI Pulse Summary, she says it found that “91% of leaders say data security, privacy and risk considerations will shape their AI strategies over the next six months.”
As in any relationship, trust is everything.
Shears closed, “Our experience as Client Zero has reinforced that scaling AI requires trust at the same time. That balance between speed and responsibility is where sustainable value is created.”
