Advantage Solutions Appoints Bethany Miles Chief AI Officer to Lead Enterprise Strategy

Advantage Solutions has appointed Bethany Miles as Chief AI Officer, the company said in a LinkedIn announcement. She will report directly to CEO Dave Peacock and lead the company’s enterprise AI strategy across operations, client services, and internal capabilities.

Miles previously held senior technology and transformation roles at Sage and Cerner, which is now part of Oracle Health. The company said she will focus on embedding AI across its business, improving the insights delivered to clients, and building systems tied to measurable performance outcomes.

CEO Dave Peacock said in a separate post that Miles had already helped shape the company’s AI direction in a prior role as Chief of Staff before taking on the new position.

The appointment comes as the company positions itself around “AI-powered commerce,” with a focus on applying AI directly to brand and retail execution rather than standalone tools or products.

AI Strategy Moves Into Execution Layer

Advantage Solutions operates as a sales, marketing, and retail services partner for consumer brands and retailers, placing it inside day-to-day commercial workflows such as merchandising, promotions, and shopper engagement. The company’s AI strategy is structured around those operational layers.

Its announcement emphasizes embedding AI across workflows, which aligns with broader enterprise shifts toward integrating AI into marketing and execution systems. AI is increasingly used to connect data, decision-making, and campaign performance in real time, particularly in retail and consumer environments.

The scope of the Chief AI Officer role reflects that transition. Responsibilities typically include aligning AI systems with business outcomes, deploying models across departments, and ensuring that outputs translate into measurable results. In this case, the company tied the role directly to client-facing impact, including insights delivered to brands and retailers.

The emphasis on measurable performance signals a focus on execution rather than experimentation. AI systems are expected to support pricing, promotions, assortment planning, and in-store or digital engagement, where outcomes can be tracked through sales, conversion rates, or campaign effectiveness.

This shift also reflects a broader move from analytics dashboards toward automated or semi-automated decision systems. Enterprise AI deployments increasingly extend beyond reporting into workflow-level actions such as recommendations, optimization, and execution triggers.

Leadership Role Formalizes Enterprise AI Function

The creation of a Chief AI Officer role places AI alongside other enterprise functions such as technology, data, and operations. Companies have begun formalizing AI leadership to coordinate infrastructure, talent, governance, and deployment across business units.

In Advantage Solutions’ case, the appointment builds on existing internal work rather than introducing a new direction. Peacock said Miles had already contributed to defining the company’s AI roadmap, indicating that the role is intended to scale ongoing initiatives rather than initiate them.

The company also framed the move as an investment in leadership, talent, and infrastructure. That combination suggests a multi-layer approach that includes model development, data systems, and operational integration, rather than isolated pilots.

Within marketing and retail environments, AI systems are increasingly tied to audience segmentation, demand forecasting, and campaign optimization. These use cases rely on integrating data from multiple sources and applying models directly within execution workflows, where outputs can influence real-time decisions.

The appointment reflects how services firms are adapting AI for applied use cases inside client operations. Instead of building standalone AI products, companies in this category are embedding models into existing processes that support revenue generation and customer engagement.

Advantage Solutions’ structure places it between brands and retailers, which gives it access to both supply-side and demand-side data. The effectiveness of its AI strategy will depend on how that data is integrated into systems that support execution at scale.

The company said the goal is to build capabilities that deliver consistent performance improvements for its clients.