A multinational data center infrastructure provider aimed to boost its Generative AI strategy. The focus was on defining an operating model, piloting a key use case, and creating a roadmap for scalable AI solutions.

Client background

A multinational provider of infrastructure for data centers was looking for AI solutions for internal and external use. Its goal was to accelerate its Generative AI (GenAI) strategy by defining an operating model and architecture, quickly piloting a “no-regrets” use case, and creating a roadmap to implement scalable GenAI solutions for further prioritized use cases.

Solution

• New sales AI solution that searches internal and external sources to generate a report on potential clients
• Broad AI use-case backlog, a sequenced implementation roadmap, and a quantification of potential benefits
• Effective Generative AI strategy, operating model, and governance structure in alignment with the company's strategic priorities
• A reference architecture that supports the development and deployment of GenAI solutions

Outcome

• $1 million estimated annual productivity savings from the sales AI solution
• More than 180 use cases ideated globally
• 22 high-impact use cases identified and prioritized for potential near-term development, with an estimated $191 million of annual business value projected from the backlog of prioritized use cases
• A fully functional operating model capable of effectively identifying, prioritizing, developing, and integrating AI solutions

A media company faced competitive pressure from emerging content generation tools. To stay ahead, the client needed to assess market fit, adapt their product portfolio with GenAI features, and explore new revenue opportunities.

Client background

The rise of Generative AI put a US-based, publicly traded company under significant competitive pressure as its core offering was competing with emerging multimedia content-generation tools. To stay ahead of impending disruption, the client needed to assess product market fit, adapt its product portfolio through investments in building GenAI into product features, and explore new nontraditional revenue opportunities.

Solution

• Targeted primary and secondary market research to evaluate the potential to monetize data assets as training data for GenAI models and build new GenAI-enabled product offerings
• Embedded capacity-based UI/UX team development team into the client's product team to rapidly integrate GenAI capabilities into existing products to increase engagement and perceived value
• Provided UX, UI, and back-end development capabilities to rapidly develop and launch a novel Generative AI product to complement the client's existing product offerings and drive additional user engagement based on the selected large language model

Outcome

• Clear view of the likely disruption to the client's business from GenAI and the strategic choices required to navigate market pressures and to identify possible paths to transform the company to capture the next wave of growth
• Critical insights to help shape client's investment decisions toward GenAI extension opportunities for existing products and new, nontraditional revenue opportunities to pursue
• Multiple waves of Generative AI product launches driving new revenues and market feedback to inform future investment areas

A large nonprofit health care network partnered with Deloitte to establish an AI center of excellence (CoE). The CoE supports use-case prioritization, governance, 
and democratized AI innovation with trust at the forefront.

Client background

To further its mission of elevating care and improving efficiency, a large nonprofit health care network engaged Deloitte to help it stand up an AI center of excellence (CoE). The CoE was designed to support use-case prioritization, governance to guide decision-making, and an operating model to align stakeholders. The results were democratized AI innovation, clarified responsibilities, and embedded trust.

Solution

• A blueprint and operating model structure for an AI center of excellence
• Identification of capabilities needed to stand up a center of excellence and scale AI programs
• Value-case narrative outlining the case for a center of excellence and corresponding execution roadmap

Outcome

• AI CoE value proposition, governance structure, and operating model
• Organization-wide process to vet, prioritize, invest, and scale AI use cases
• Trustworthy AI approach for use-case validation and responsible AI deployment to accelerate innovation safely
• Defined path to scale and develop critical next steps to launch AI initiatives