Embracing AI with a Business-Driven Approach
Embracing AI with a Business-Driven Approach
Even when new innovations offer clear benefits, spreading them throughout an organization can be difficult, especially if the innovation disrupts current work methods. By experimenting with generative AI capabilities, companies can achieve early successes and develop change agents and opinion leaders. This helps increase acceptance and spread the innovation further, kick-starting transformation and reskilling efforts.
Organizations need to adopt a two-pronged approach to experimentation:
- Quick Wins: Focus on easy-to-achieve opportunities using ready-to-use models and applications to realize quick returns.
- Business Reinvention: Concentrate on reinventing business, customer engagement, and products and services using models customized with the organization’s data. A business-driven mindset is crucial to define and successfully deliver on the business case.
As they experiment and explore reinvention opportunities, they’ll gain tangible value while learning more about which types of AI are best suited to different use cases. They’ll also be able to test and improve their approaches to data privacy, model accuracy, bias, and fairness, and learn when “human in the loop” safeguards are necessary. A staggering 98% of global executives agree that AI foundation models will play a significant role in their organizations’ strategies in the next 3 to 5 years.
Investing in People and Training for AI Success
Success with generative AI requires as much focus on people and training as it does on technology. Companies should significantly increase investment in talent to address two distinct challenges: creating AI and using AI. This means both building talent in technical competencies like AI engineering and enterprise architecture and training people across the organization to work effectively with AI-infused processes. For instance, in our analysis across 22 job categories, we found that LLMs will impact every category, ranging from 9% of a workday at the low end to 63% at the high end. More than half of working hours in 5 of the 22 occupations can be transformed by LLMs.