PwC’s learning team is spearheading an ambitious initiative that will integrate gen AI across its workforce. In 2023, the firm announced a $1 billion investment to expand and scale its artificial intelligence offerings. The program includes a commitment to upskilling over 75,000 U.S. employees, equipping them with the tools and knowledge needed to harness AI’s capabilities and explore potential uses for clients.

This investment aligns with insights from the firm’s 2025 AI Business Predictions report, which highlights AI’s ability to deliver small efficiencies and transformational shifts in the workplace. The report emphasizes the critical need for businesses to adopt AI strategically and responsibly to remain competitive—an approach reflected in PwC’s commitment to its own workforce.

After a year-and-a-half of applying its generative AI strategy, here’s what PwC has learned from both research and hands-on experience.

Related: PwC’s HR, tech leaders prepare to train U.S. workforce on ChatGPT technology

Small gains and groundbreaking innovations

PwC researchers emphasize two main drivers of AI’s potential: incremental improvements and major innovations. According to the report, systematic application of AI can yield 20%–30% boosts in productivity, speed and revenue, contributing significantly to operational efficiency. On a larger scale, developing entirely new AI-driven business models can lead to transformative changes that redefine industries and create significant competitive advantages.

However, such changes are complex, and a successful AI strategy requires a diverse and multi-tiered approach. PwC recommends categorizing initiatives into three levels: small, quick wins referred to as “ground game”; ambitious but realistic projects, called “roofshots”; and high-risk, high-reward efforts, labeled “moonshots.” According to PwC, leadership must be actively ensuring that AI technology use is strategically aligned with broader organizational objectives.

Differentiating with gen AI governance

According to PwC, true differentiation in AI implementation lies in leveraging proprietary data and institutional knowledge, not simply choosing the most advanced large language model. Governance is also critical as businesses increasingly rely on AI for core operations.

PwC also emphasizes the importance of proactively managing risks, implementing independent oversight, and ensuring accountability and trust in the use of AI. Given AI’s rapid evolution, companies cannot afford to wait for regulatory clarity, according to PwC report authors.

AI is already delivering transformative results in specific industries, according to PwC. In research and development, AI can reduce costs by 30% and cut time-to-market by 50%, driving efficiency and innovation. In pharmaceuticals, AI has cut drug discovery timelines in half, revealing its potential to accelerate breakthroughs.

Beyond industry-specific applications, AI plays a key role in sustainability by automating data collection, optimizing supply chains, streamlining regulatory compliance and supporting low-carbon product initiatives, write the report’s authors.

The PwC report stresses the importance of adopting AI now, yet the unprecedented speed of AI innovation demands a phased approach that balances immediate wins with ambitious projects. This approach—combined with strong governance practices—ensures businesses can achieve long-term success while adapting to rapid technological advancements, according to PwC researchers.

PwC’s $1B gen AI investment

The consulting firm is leading by example. In April 2023, PwC announced a $1 billion investment over three years to scale its AI capabilities and upskill its workforce. Leah Houde, PwC’s chief learning officer, describes the initiative as a commitment to transforming employees into “savvy, responsible users of gen AI.”

Houde explains that while traditional learning methods often involve passive consumption, this program focuses on active engagement. Called My AI, it integrates generative AI tools, training and practical experience to build skills alongside enthusiasm.

To encourage innovation, PwC created a “playground” where employees can experiment with new use cases, says Houde, allowing them to break free from traditional learning approaches and foster creativity.

Social learning builds engagement

The firm also has prioritized social learning, developing workshops that teams can run independently or with facilitation from expert “superstar” users. Since launching, the workshops have garnered over 800 requests, with more than 500 already completed, according to Houde.

Houde notes that the workshops’ collaborative nature has inspired employees to discover innovative applications of generative AI, which they can directly incorporate into their work.

PwC’s approved tools, Microsoft Co-Pilot and ChatPwC—both secure, private and domain-trained access to OpenAI’s technology—are made available to the workforce within strict responsible use guidelines. Houde says that by the end of 2023, 95% of employees had engaged with gen AI in some capacity and some employees are using advanced versions of these tools to address specific challenges.

PwC prompting parties

To drive broader adoption and creativity, PwC has introduced “prompting parties,” real-time brainstorming sessions where employees can experiment with generative AI in a risk-free, collaborative environment. These have been instrumental in fostering a positive culture around AI adoption through hands-on learning, Houde says. “Get people in there playing; hands-on is the way to deal with this one,” she advises.

As PwC continues to move forward with its AI investment and strategy, the focus is shifting to refining AI applications to solve specific client problems. The initiative already has cultivated a growing willingness among employees to experiment with new tools, leading to frequent “cool outcomes,” according to Houde.

The learning executive attributes this success to the firm’s emphasis on practical, hands-on engagement: “The pace of innovation has been rapid, and we are running L&D strategy in sprints—months, not years.”

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