RGP's Strategic Rebalancing: Can AI-Driven Transformation and Cost Discipline Fuel a Turnaround?

In the high-stakes arena of professional services, Resources Connection (RGP) has embarked on a dual-track strategy to navigate a turbulent market: aggressive cost discipline and a bold pivot toward AI-driven transformation. As the firm enters 2025, the question looms: Can these efforts catalyze a sustainable turnaround? The answer hinges on RGP's ability to bridge the gap between AI ambition and operational readiness while maintaining fiscal rigor.

Strategic Restructuring and Cost Discipline: A Foundation for Stability

RGP's restructuring initiatives from 2023 to 2025 have prioritized cost optimization and operational efficiency. A U.S. Restructuring Plan launched in October 2023 . By early 2026, these efforts had , driven by reduced employee compensation, technology transformation, and streamlined business support costs. Such measures reflect a disciplined approach to fixed-cost management, aligning with broader industry trends where professional services firms are redefining talent strategies to prioritize AI fluency and data literacy.

The firm's focus on value-based pricing and improved consultant utilization also underscores a shift toward profitability-centric models. These steps are critical in an industry where 78% of organizations use AI in at least one function, . By reallocating capital from traditional hiring to technology and automation, RGP is positioning itself to compete in a landscape where client-facing DIY AI solutions threaten to erode margins.

AI Adoption: Promise and Peril in Professional Services

RGP's AI initiatives, however, reveal a stark divide between ambition and execution. While within two years, only 14% report meaningful value today. This gap is exacerbated by systemic challenges: as a barrier to AI readiness, and 68% highlight skills shortages as a major obstacle. In financial services-a sector where AI spending is projected to reach $97 billion by 2027-these hurdles are compounded by regulatory scrutiny and the need for frameworks.

Yet, RGP's research identifies pockets of progress. For instance, AI-powered virtual assistants in banking have , allowing relationship managers to focus on high-value tasks. Similarly, AI-driven contract intelligence systems have accelerated loan documentation, while generative AI in trade surveillance has improved anomaly detection. These applications demonstrate AI's potential to enhance efficiency, but their scalability depends on modernized data architecture and governance frameworks.

Bridging the Divide: Strategic Synergies

The interplay between RGP's cost discipline and AI adoption is where the firm's turnaround potential crystallizes. Cost reductions free up capital for AI investments, while AI-driven automation amplifies the impact of those savings. For example, RGP's 2025 restructuring efforts included a , achieved through streamlined fixed costs and higher bill rates.

Concurrently, AI has . These metrics suggest a virtuous cycle: disciplined cost management funds AI innovation, which in turn drives further efficiency gains.

However, success hinges on addressing foundational weaknesses. RGP's emphasis on governance-first approaches-such as reusable AI frameworks and cross-functional talent strategies-is a step in the right direction. Yet, with , the firm must prioritize data modernization and workforce upskilling to close the AI readiness gap.

The Road Ahead: A Calculated Bet

RGP's strategic rebalancing is neither a silver bullet nor a guaranteed success. The firm's ability to navigate the AI inflection point will depend on its capacity to align technology with client outcomes, regulatory expectations, and internal capabilities. While large enterprises outpace mid-market firms in AI ROI confidence, RGP's focus on governance and performance-driven metrics-such as forecast accuracy and risk reduction-positions it to compete.

For investors, the key takeaway is clear: RGP's turnaround is plausible but conditional. If the firm can sustain cost discipline while overcoming AI adoption barriers, it may emerge as a leader in the AI-driven professional services sector. However, delays in modernizing data infrastructure or addressing skills gaps could widen the competitive divide, jeopardizing long-term value creation.