Innovating Internal Automation Efficiency

Microsoft is showcasing how AI can internally transform businesses. By widely adopting its Microsoft 365 Copilot solution, global companies like Barclays and Indra Group are redefining workplace productivity. This isn't just a software upgrade; it's a strategic shift aimed at optimizing human capital and reallocating work hours to higher-value tasks. AI acts as an agent that frees employees from routine duties, enabling them to focus on solving complex problems and having high-quality interactions with customers.

The large-scale rollout of Microsoft 365 Copilot to 100,000 employees at Barclays and the high 80% adoption rate at Indra Group aren't just minor software improvements; they're a time-optimization strategy. The ability of AI agents to perform tasks that were once very time-consuming—such as analyzing legal files, which in ILUNION's case was cut down to just 40 seconds—has direct, quantifiable financial implications. The documented savings of over 7,000 annual work hours for ILUNION translates into a significant reduction in operational costs, which can be measured in salaries and personnel expenses.

Beyond immediate efficiency, this approach increases profitability per employee. By freeing up talent from low-value tasks, companies let them concentrate on innovation, customer relations, and business strategy. This not only boosts overall productivity but also helps retain specialized talent, which is crucial for long-term success. Redirecting staff toward higher-value activities directly impacts business profitability, strengthening AI's role as a driver of sustainable growth rather than just a cost-saving tool.

Recommendations

• Co-creating Processes with Internal AI: Product/R&D teams should assess how internal AI can be integrated into their development cycles. This includes creating custom "AI agents," such as the "Indra M365 Copilot Helper," to automate initial market research, generate code prototypes, or draft technical documentation. The goal is to shorten delivery times for new products and free up engineers and designers to focus on innovation and solving complex design problems, ensuring that product development stays agile and competitive.

• Productivity Audits and AI Deployment at Scale: The Finance and Strategy departments should lead a productivity audit to pinpoint internal processes with the most potential for AI optimization. The Technology team, in collaboration with Human Resources, needs to develop a plan for the large-scale deployment of AI solutions. This plan should not only focus on acquiring the technology but also on providing training and support to ensure a high adoption rate, similar to what the Indra Group achieved. The ROI should be measured not just by time saved, but also by improvements in overall performance and the revaluation of corporate talent.

• Re-engineering Workflows Focused on Human Value: Operations and Service teams should redefine workflows to make the most of the time freed up by AI. For instance, instead of having customer service staff answer FAQs, an AI could handle those inquiries, allowing human agents to focus on more complex interactions, such as resolving high-impact complaints or proactively identifying cross-selling opportunities. The key metrics to track will be more than just efficiency; they will include improved customer satisfaction, reduced churn, and better retention.