A public administration has responsibly used the latest digital technologies to quickly and at scale automate certain processes, thus saving 3 million man-hours in Operations.
A bank delivered hyper-personalized offers to 16 million customers just three months after implementing a generative AI-powered marketing solution.
An insurance company is reinventing its entire underwriting workflow. The potential revenue increase is 10%.
It's not enough to look at individual use cases. We need to understand the potential to reinvent the entire value chain and develop end-to-end capabilities powered by generative AI and new ways of working.
Let the value generated by every business capability reinvented with generative AI guide you.
Identify strategic choices where technology opens up new opportunities that competitors cannot easily capture.
Redesign your organization from siloed functions to end-to-end business and decision-making capabilities, leveraging a unified data architecture and cross-departmental teams.
Realizing the potential of personalized medicine requires a new way of working that overcomes barriers along the patient care cycle. Roche is building platforms that aggregate data from various sources. One such platform is the Oncology Hub, which allows for the secure management of all patient data and provides medical staff with a single, centralized workspace for collaboration. This helps initiate the treatment journey faster, saving more lives.
Examine your technology objectively to understand where your “digital core” stands compared to the industry and, most importantly, what is needed to use generative AI.
Learn more about the concept of a data and generative AI backbone and what you need to build it.
Ensure your CIO integrates cybersecurity practices early in the technology lifecycle. Create a strong security culture to prioritize resilience.
Understand your current technology and advisor ecosystem and update your strategy on how to best collaborate with them to accelerate reinvention.
Rigorously measure progress: More than 50% of technology investments must go toward building new capabilities.
This client has enormous volumes of data in various formats and generates new data every day. After holistically assessing its needs and challenges, the company implemented generative AI and cognitive search to fully extract the value of its data and generate growth. Today, the new knowledge base incorporates over 250,000 documents and easily retrieves the necessary information by converting it into the desired format. This new integrated configuration makes it much easier to find information, automates the data collection process for various business users, and helps reduce errors.
Create a talent strategy that identifies how work will change, documents the impact on different roles, and assesses which skills are needed for each generative AI use case.
Build strong, people-centric change management capabilities to understand the impact of generative AI on every aspect of the employee experience.
Develop the capacity to offer ongoing training to support reinvention. Ensure your people have relevant skills for the generative AI market and are actively involved in the change.
Analyze your HR capabilities and invest in the skills and technologies needed to support your business reinvention strategy. Human resources management is a fundamental part of your business strategy.
Review your employee value proposition to ensure you're still the best company for your people. Also, ensure your use of generative AI is consistent with your commitments to your people.
Aiming to become the leading research-intensive organization specializing in the discovery and development of new therapies, this client is creating new types of training and experiences for its leaders to help foster an innovative, entrepreneurial mindset. This includes engaging people in process design, an upskilling program for thousands of internal resources to make them generative AI experts, and hiring new talent with the right skills.
Adopt principles for responsible AI, with clear accountability and governance for design, implementation, and use.
Conduct an AI risk assessment: Understand the risks of existing AI use cases, applications, and systems through qualitative and quantitative assessments.
Conduct continuous and systematic testing of AI to ensure fairness, transparency, accuracy, and safety, using the best tools available, and implementing mitigation measures.
Establish continuous monitoring of AI systems and oversee responsible AI initiatives while implementing containment and compliance measures.
Engage all business functions in AI adoption to assess impacts on people, regulatory compliance, sustainability, and privacy and security programs.
The Monetary Authority of Singapore (MAS), the Asian nation's central bank, is one of the first financial regulators to implement a responsible AI program. The Authority established the Veritas industry consortium to help financial services institutions (FSIs) assess the alignment of their AI and data analytics solutions with the principles of fairness, ethics, accountability, and transparency. A core team within Veritas has developed a methodological framework to operationalize these principles. This helps FSIs derive value from AI responsibly and build a more equitable future for billions of consumers worldwide.