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  1. AI For Pharma Growth
  2. E199: Podcast with Cures & Capital Part 2
E199: Podcast with Cures & Capital Part 2

E199: Podcast with Cures & Capital Part 2

AI For Pharma Growth · Jan 7, 2026

Pharma's AI revolution is stalled by strategy fragmentation, not tech. Win by connecting isolated pilots into an enterprise-wide capability, led from the board.

AI Strategy Is a Board-Level Responsibility, Not an IT Delegation Task

Treating AI as a technology initiative delegated to IT is a critical error. Given its transformative impact on competitive advantage, risk, and governance, AI strategy must be owned and overseen by the board of directors. Board ignorance of AI initiatives creates significant, potentially company-ending, corporate risk.

E199: Podcast with Cures & Capital Part 2 thumbnail

E199: Podcast with Cures & Capital Part 2

AI For Pharma Growth·a month ago

Pharma's AI Battle Will Be Won by Integrating "Pockets of Excellence," Not by Creating Them

Many pharma companies have breakthrough AI results in isolated functions, or "pockets of excellence." However, the ultimate competitive advantage will go to the company that first connects these disparate successes into a single, integrated, enterprise-wide AI capability, thereby creating compounded value across the organization.

E199: Podcast with Cures & Capital Part 2 thumbnail

E199: Podcast with Cures & Capital Part 2

AI For Pharma Growth·a month ago

Pharma CFOs Must Adopt New ROI Models for AI's "Investment Paradox"

AI requires significant upfront investment with uncertain returns, creating an "investment paradox" for CFOs. Traditional ROI models are insufficient. A new financial framework is needed that measures not just cost savings but also revenue acceleration, risk mitigation, and the strategic option value of competitive positioning.

E199: Podcast with Cures & Capital Part 2 thumbnail

E199: Podcast with Cures & Capital Part 2

AI For Pharma Growth·a month ago

Build an Effective AI Strategy by First Ignoring AI and Focusing on Core Business Problems

Successful AI strategy development begins by asking executives about their primary business challenges, such as R&D costs or time-to-market. Only after identifying these core problems should AI solutions be mapped to them. This ensures AI initiatives are directly tied to tangible value creation.

E199: Podcast with Cures & Capital Part 2 thumbnail

E199: Podcast with Cures & Capital Part 2

AI For Pharma Growth·a month ago

Pharma's AI Failures Stem from Strategic Fragmentation, Not Technical Shortcomings

Companies run numerous disconnected AI pilots in R&D, commercial, and other silos, each with its own metrics. This fragmented approach prevents enterprise-wide impact and disconnects AI investment from C-suite goals like share price or revenue growth. The core problem is strategic, not technical.

E199: Podcast with Cures & Capital Part 2 thumbnail

E199: Podcast with Cures & Capital Part 2

AI For Pharma Growth·a month ago

Prioritize AI-Ready Data for Strategic Wins, Not an Exhaustive Company-Wide Cleanup

The impulse to make all historical data "AI-ready" is a trap that can take years and millions of dollars for little immediate return. A more effective approach is to identify key strategic business goals, determine the specific data needed, and focus data preparation efforts there to achieve faster impact and quick wins.

E199: Podcast with Cures & Capital Part 2 thumbnail

E199: Podcast with Cures & Capital Part 2

AI For Pharma Growth·a month ago