The benefits of AI for businesses are almost infinite, and constantly evolving as the technology advances: more efficient operations, more productive employees, greater customer satisfaction, revenue growth through  new products and services—the list goes on.  But businesses will see the biggest impact from AI when they scale it across the organization in a responsible, ethical way. When enabled by cloud, and driven by data, AI is the differentiator that helps businesses make faster, smarter, decisions that help change organizations and enable growth—at scale, while also benefitting the people it intends to serve.

There is no set way to do AI implementation, and use cases can range from the relatively simple (a retailer lowering costs and improving experience with an AI chatbot) to the highly complex (a manufacturer monitoring its supply chain for potential issues and fixing them in real-time). However, there is an AI roadmap, with some fundamentals that organizations should consider to set themselves up for success. It's critical to align AI strategy with business goals and to choose the right operating model and capabilities to support those goals.  Organizations also need to reconfigure their workforce to support and scale AI. That means defining the optimal talent mix to deliver business outcomes, while facilitating hiring, upskilling and cultural change to empower employees. Finally, considerations for AI must be built into an organization's core values as well as their governance and compliance processes. That includes implementing technical guidelines to make sure that AI systems are safe, transparent and accountable, and training everyone in the organization, from general employees, to AI practitioners, to the C-suite, to use AI with context and confidence.

AI-as-a-service refers to pay-as-you-go AI services and solutions that are pre-configured on cloud and ready to implement. This allows the client to experiment with AI use cases and prove value before they make any large capex or opex investments to scale AI. By tapping into the AI service provider’s learnings and experiences, tech and talent, clients get the required functionality at a lower cost and greater speed than if they built the capabilities themselves.