Organisations investing in artificial intelligence earn significant profits, with generative AI delivering an average return on investment of $3.70 per dollar spent, and some companies achieving up to $10, according to The Business Opportunity of AI, an IDC study commissioned by Microsoft. “For customers to understand the business opportunity of AI, they need to see how it can directly impact their top and bottom line,” says Sam Murley, general manager of industrial AI and strategic partnerships at Microsoft. “We work closely with customers to identify the practical benefits of AI for their business, such as increased efficiency, cost savings and differentiation through innovation that creates new revenue streams. “Successful AI adoption occurs when customers prioritise connecting AI initiatives to their profit and loss. They clarify the goals of AI and communicate the purpose of these changes before focusing on implementation. One of the most effective ways to accelerate adoption of AI initiatives is by capturing business value across scale and multi-year deployments, creating proof of value in the near term, and leveraging lighthouse locations to demonstrate feasibility and business impact against high-priority scenarios.” Cross-industry impact Murley outlines three essential steps for successful AI transformation: maintaining strong security standards, consolidating data and prioritising a human-centric approach to innovation. “Ensuring robust security measures is paramount as organisations integrate AI into their operations, safeguarding sensitive data and maintaining trust,” says Murley. “Data harmonisation and creating an AI-ready data estate are critical for deriving actionable insights. This involves integrating diverse data sources in a secure and compliant way, standardising data formats and ensuring data quality and accessibility. Lastly, a human-centric approach to AI innovation focuses on enhancing user experiences and driving meaningful outcomes, ensuring that technological advancements align with human needs and ethical considerations. These themes collectively drive successful AI transformations, enabling industries to harness AI’s potential while maintaining security and fostering innovation.” Organisations across industries also need to implement AI solutions that address their specific needs and use cases. “Industry-specific AI models can significantly enhance organisational efficiency by leveraging domain-specific knowledge and data to tailor solutions that address unique challenges and opportunities within a particular industry,” explains Murley. “Because these models are trained on data that is highly relevant to the industry, they allow for more accurate and context-aware insights. This customisation ensures that the AI solutions are directly applicable to the organisation’s operations, leading to more effective decision-making.” For example, medical professionals at Chi Mei Medical Center in Taiwan are serving double the number of patients per day with help from a generative AI assistant built on Microsoft’s Azure OpenAI Service. Two-thirds of the pharmacists are using A+ Pharmacist copilot to summarise patients’ clinical information from multiple databases including medication lists, surgical records, allergy history, lab tests and medical records. According to Hui-Chen Su, head of the pharmacy department at the centre, the copilot means one pharmacist can see 30 patients per day rather than 15. This allows pharmacists to spend more time caring for patients with complex needs. “ One of the most effective ways to accelerate adoption of AI initiatives is by leveraging lighthouse locations to demonstrate feasibility and business impact against high-priority scenarios” 39
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