Despite early investments in AI, this global technology company faced growing AI adoption challenges that limited its ability to generate tangible results. While multiple solutions had been deployed, the business was not seeing the expected return—creating pressure to justify AI spend and demonstrate impact.
Key AI adoption challenges included:
The business needed to move beyond isolated AI deployments toward a cohesive strategy that connects use cases to outcomes and embeds AI into day-to-day operations.
Building on a long-standing partnership, the client worked with Concentrix to overcome these AI adoption challenges. The focus was not on adding more AI, but on activating value from what already existed. Our approach combined real-world observation with data-driven analysis:
Near-term value (high impact, high feasibility):
Next-wave opportunities (higher complexity, higher upside):
To ensure execution, the strategy also addressed technology alignment by validating that it fit with existing platforms; data and content readiness by improving structure, accessibility, and the integration of knowledge assets; and change and adoption by embedding AI into workflows to drive sustained usage.
We identified 12 unique use cases for Al to enhance advisor efficiency and utilization, using successful examples from other Al implementations across similar clients to provide a benchmark for success.
9.5% productivity gains across prioritized workflows.
44% projected adoption rates for near-term use cases.
$5-7M in annualized cost savings identified.
$2-3M in new revenue potential through improved conversion and efficiency.
Rather than scaling AI for its own sake, the client shifted to scaling outcomes, connecting AI directly to adoption, productivity, and revenue impact. This approach to its AI adoption challenges demonstrates a broader shift: success in AI is no longer defined by deployment, but by how effectively it is embedded into operations to overcome AI adoption challenges and translated into measurable business performance.
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