PwC: Surveyed Institutions Have Already Achieved 10%-15% Returns from Initial AI Investments

AI Investment Returns Up to 15% — Why Is There Still a Budget Shortfall?

Beijing News Shell Finance Report (Reporter Chen Weicheng) — On March 17, PwC released the report “AI Boosts Innovation and Upgrades in China’s Mainland and Hong Kong Financial Services Industry,” which shows that 76% of financial institutions plan to use AI to achieve business transformation and help develop new revenue streams; surveyed organizations have already seen preliminary returns of 10%–15% from AI investments.

PwC China Management Consulting Partner Wang Jianping stated, “Organizations surveyed have already gained initial returns of 10%–15% from AI investments. While they focus on short-term gains, they also place greater emphasis on AI’s long-term value in enhancing market position, expanding strategic development space, and creating new growth opportunities. However, the core issue is whether the investment effort is sufficient — the survey shows that 61% of financial institutions allocate less than 10% of their technology budgets to AI, indicating a 30%–40% gap between AI investment and actual demand within the industry.”

Respondents said that the investment returns from their AI projects are reflected in risk reduction, improved compliance efficiency, increased revenue, and cost savings. The report also emphasizes the importance of human-machine collaboration: 57% of organizations are using AI to enhance existing employee functions. AI applications tend to complement human capabilities rather than replace employees.

Qing Ni, Partner in Charge of Asset and Wealth Management Industry at PwC China, said, “Different industries focus on different AI deployment applications. Banks mainly focus on risk control, anti-money laundering, and compliance tasks, while insurance companies emphasize agent skill enhancement, customer service, and claims processing. In asset and wealth management, AI is applied to investment and portfolio management, data analysis, and market analysis.”

The report also points out that large-scale AI adoption still faces multiple constraints. Talent shortages and rigid organizational structures are the main barriers to large-scale AI deployment, with impacts far exceeding budget or technical issues. The survey shows that only 29% of financial institutions have successfully built an “AI-first” culture. It is worth noting that AI implementation cannot rely solely on technical capabilities; cultural transformation is equally essential. Additionally, traditional processes and siloed functions continue to hinder AI promotion.

Li Weibin, Partner at PwC China Management Consulting, said, “Respondents generally report that a major challenge they face is recruiting ‘hybrid’ professionals who understand both business and algorithms. Training and upskilling existing staff, as well as establishing incentive mechanisms that encourage AI as a transformation tool, are crucial for building an AI-first culture. Equally important is that senior management lead by example and actively promote AI applications.”

Beyond talent and organizational culture, data remains a key constraint. Respondents identified three major obstacles to increasing AI investment: data availability (30%), regulatory pressure (20%), and the need to prioritize maintaining existing core systems (14%). Data security and privacy protection are the top challenges in data management, leading 90% of financial institutions to rely on proprietary internal data to support AI applications.

Wang Jianping believes, “Financial institutions have high expectations for AI to empower their businesses. They see AI’s value not only in improving operational efficiency but also as a critical opportunity to reshape AI-native business models, reconstruct service experiences, and innovate business approaches — opportunities that must not be missed.”

Editor: Yang Juanjuan

Proofreader: Yang Lì