The New Automation Mindset: AI + Automation + Integration

Bain's Michael Heric is Bridging Innovation and Tradition in Automation

May 21, 2025

Michael Heric, a Senior Partner at Bain & Company, shares his extensive 25 years of expertise in enterprise automation. He discusses the shift from traditional RPA to the age of generative AI, highlighting its impact on workplace efficiency. Michael explores the challenges corporate back offices face, particularly in data management and adoption hurdles. He emphasizes the need for structured change management and iterative approaches in leveraging AI, while also touching on the exciting potential of AI agents in enhancing collaboration and productivity.

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INSIGHT

BPOs Must Adapt to AI

BPOs face rising pressure due to AI automation and must evolve their business models.
The future market leaders in outsourcing may differ due to AI's rapid innovation pace.

ANECDOTE

Bain's Early AI Adoption Stories

Bain is a leading adopter and tester of generative AI internally and with clients.
Examples include Coca-Cola's marketing and Target's AI-driven customer tools.

ADVICE

Address Barriers to AI Adoption

Overcome AI adoption challenges by addressing data access, integration, trust, and governance.
Manage fears around job impact through effective change management.

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In this episode, Markus sits down with Michael Heric, Senior Partner at Bain & Company and leader of Bain’s global automation capabilities, to explore how enterprise automation has evolved from traditional RPA to the era of Generative AI and intelligent agents. With 25 years of industry insight, Michael shares a compelling roadmap for leveraging automation at scale, drawing from real-world client experiences and internal Bain initiatives. From the early challenges of BPR to the promises and pitfalls of AI adoption today, this episode offers a grounded, strategic perspective for enterprise leaders navigating digital transformation.

Timestamps

00:00 Episode Start

02:45 History of workplace automation

06:00 Finding the right tool at the right time

13:35 Change management at scale

16:15 Who ends up implementing these new toolsets?

18:20 Challenges and success stories from real organizations

21:45 Getting ROI by learning from the past

24:10 Some underrated use cases for LLMs

26:50 Putting trust in GenAI toolsets

29:20 Are organizations ready from a data perspective?

32:45 Adapting at the same rate the world is changing

40:05 Leveraging AI to create better products

44:20 Conclusion and final thoughts

Episode Key Takeaways

The opportunity still exists in the back office: Despite clear value potential, finance, HR, and legal remain under-automated due to data, trust, and auditability concerns. These areas are poised for transformation with the right approach.
Success depends on sticking with it: Many organizations fail not because their data or ideas were worse, but because they gave up too early. The companies winning with AI are the ones that iterate and persevere.
Apply innovation where you have gaps: Don’t waste generative AI on processes that already work with existing automation. Focus on "white space" opportunities—areas where older tools failed or never reached.
Use the right tool for the job: Traditional automation (like RPA) still delivers value in structured, rule-based tasks, while AI agents excel in dynamic, ambiguous environments like customer service and sales.

Top Quote

"Doing business process redesign, even doing some of these large ERP implementations…the world is moving so fast, these business processes are changing. By the time you’re done with the redesign, the world’s already moved past it. So you're constantly multiple steps behind. And I think now we're finally getting to a spot where technology can be flexible enough to adapt at the same rate the world is changing."

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