I lead IBM Consulting, here’s how AI-first companies must redesign work for growth

I lead IBM Consulting, here’s how AI-first companies must redesign work for growth

https://fortune.com/2026/01/19/i-lead-ibm-consulting-heres-how-ai-first-companies-must-redesign-work-for-growth/

Publish Date: 2026-01-19 08:30:00

Source Domain: fortune.com

• Expectations for AI Revenue: Nearly 80% of executives anticipate AI will significantly contribute to revenue by 2030, though only a small portion knows the source of that revenue.

• Architectural Differentiators: Companies that are leading in AI implementation are not simply adapting AI to legacy workflows but are instead redesigning the architecture of their operations, integrating human and digital work, and reinvesting productivity savings strategically.

• Redesigning Work vs. Augmentation: There is a stark divide between organizations that merely augment existing workflows with AI, gaining marginal benefits, and those that redesign their operations to create new, inimitable growth trajectories.

• Architectural Choices:

  1. Redesign Work: Instead of automating broken processes, focus on designing new work processes that leverage both human judgment and AI capabilities.
  2. Build Proprietary Intelligence: Create custom AI models that understand and replicate specific business nuances better than generic or third-party models.
  3. Engineer Growth Loops: Treat AI-driven productivity as a fund for innovation, reinvesting gains from AI efficiency into new products, services, and markets to create exponential growth.

• Case Studies:

  • Nestlé: Rebuilding its enterprise architecture with AI to deliver superior products and build more personalized experiences.
  • Riyadh Air: Starting as a startup, building a fully AI-native operation interconnected with operations, employees, and customers.
  • L’Oréal: Developing a custom AI model based on proprietary data to maintain a competitive edge.

• Future Directions:

  • Companies must rethink their current operations based on AI-first principles, eliminating outdated workflows, creating unique AI capabilities, and reinvesting in growth instead of saving costs.

• Conclusion: Those who answer these strategic questions regarding their AI architecture and growth trajectories will dominate by 2030 in ways competitors can’t replicate.