Organizations need to redesign workflows, roles, and processes to align with new AI technologies.
First published on Inc.com on Feb. 16, 2026
With all the buzz around artificial intelligence, one might conclude that leaders need only to buy some AI tools and deploy them, then sit back and reap the rewards: greater efficiency, better data insights, and improved customer service, all delivered by a smaller workforce.
However, AI is not a plug-and-play tool that automatically boosts productivity and reduces headcounts. A 2025 MIT study found some 95 percent of generative AI pilot projects do not have a measurable impact on organizations’ bottom line, and the majority had little (if any) impact on headcount. “Most fail due to brittle workflows, lack of contextual learning, and misalignment with day-to-day operations” the study noted. Only five percent of organizations surveyed had actually integrated AI into their workflows at scale.
To reap maximum benefits, organizations need to redesign workflows, roles, and processes to align with AI technologies. A 2025 McKinsey and Company study identified redesigning workflows as a major factor in AI initiatives’ success. Enterprises cited by McKinsey as high AI performers were almost three times as likely to significantly modify their workflows. “Indeed, this intentional redesigning of workflows was one of the strongest contributions to achieving meaningful business impact of all the factors tested,” the McKinsey study added.
Align AI and people in the workplace
AI implementations are often approached as a largely technical undertaking. Enterprises may look to AI-powered chatbots and agents powered by Large Language Models to handle customer calls, automate routine tasks, or free employees to pursue more complex activities. But companies that focus too much on technology can overlook a critical component: how AI changes employees’ daily lives. Simply adding an AI chatbot on top of current workflows dilutes the potential benefits AI can provide. To get the most bang for the buck, enterprises must design new workflows to maximize human-AI collaboration.
The 2025 Work Reimagined survey by EY describes how enterprises should approach redesigning employee roles to boost employee contributions and reduce workplace tensions that can arise from AI projects. That guidance includes:
- Determine which high-value activities employees should focus on and which tasks they should turn over to AI.
- Redesign roles and workflows as a universal component of AI implementation planning, not a last-minute afterthought.
- Create feedback mechanisms to measure efficiency gains and ROI impacts.
How to integrate AI and workflows
Aligning AI, employee roles, and organizational workflows means taking a close look at current processes and employee capabilities, identifying training gaps, and determining how to best integrate AI with your organization. Early adopters like JPMorgan Chase and Mayo Clinic are showing what success looks like. Here are three examples of how to integrate AI and workflows.
JPMorgan Chase
JPMorgan Chase was one of the earliest financial services companies to embrace AI. It created the Contract Intelligence (COiN) system in 2017, which uses AI to analyze commercial loan applications, saving an estimated 360,000 in legal team hours annually. JPMorgan has since expanded its applications and modified its workflows around algorithmic trading, fraud detection, risk management, customer service, and payment validation.
In 2024, JPMorgan became the first major bank to offer Generative AI (GenAI) to employees at scale when it made its proprietary LLM Suite available to almost 250,000 employees. Last year, it allocated $2 billion of its $18 billion technology budget to AI projects, with CEO Jamie Dimon stating the AI investment brought $2 billion in benefits.
PwC
Global consultancy PwC is investing more than $1 billion to expand its GenAI capabilities across multiple business functions, including in audit, tax compliance, procurement, human resources, and talent acquisition. Its “client zero” strategy calls for PwC to implement AI-powered solutions internally first and then scale those solutions for its clients.
In 2024, the first year of its multi-year AI project, PwC reported productivity gains of 20 percent to 40 percent in the finance function; 20 percent to 30 percent in marketing; and 20 percent to 50 percent in IT. For software development and customer service, PwC applies coordinated teams of AI agents to write code, triage tickets, and elevate issues for human review. “To unlock even more value rethink how work gets done,” the report suggests. “What else can your people do when a GenAI assistant does simple work for them — and provides data and leading practices to support higher-value work?”
Mayo Clinic
Mayo Clinic has developed and deployed a variety of AI tools within its workflows to enhance diagnostics, improve patient outcomes, and foster physician collaboration. For example, at Mayo Clinical Labs, AI has transformed laboratory operation workflows by automating tasks, improving quality, and enhancing efficiency. “This transformation is not driven by hype, but by necessity,” a report about the lab states. “Rising test volumes, workforce shortages, and increasingly complex data have created an urgent need for smarter, more scalable solutions.”
Meanwhile, the Mayo Clinic Platform brings health providers, researchers, and technology developers together in an environment to access clinical data, train AI tools, and share vetted digital solutions. “Providers benefit from insights and vetted digital health tools that integrate into clinical and administrative workflows, improving diagnoses, streamlining care delivery, and reducing staff burden,” a report about the Mayo Clinic Platform states. Last year, the organization also launched Mayo Clinic Platform Insights, which provides access to the clinic’s expertise to global healthcare organizations of all sizes.
Executive takeaways
AI adoption without workflow redesign is a recipe for friction. Success depends on more than system architects and technicians. A recent survey published in the Harvard Business Review found that 47 percent of senior business leaders ranked leadership effectiveness as the biggest factor driving positive ROI for AI implementations.
Leaders must ensure that AI implementations rethink roles, workflows, and human-AI interactions to strategically unleash the enterprise’s value without eroding human engagement.
