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  • Writer's pictureJose Pierre

What's needed for AI Enterprise Transformation?

Artificial intelligence (AI) continues to be one of the most popular technologies among business executives in decades. Increased pressures on financial services organizations is driven in part by investors’ enthusiasm for digital capabilities. This has fueled the need for well-planned transformation strategies to innovate in order to enhance the customer service experience. Early adopters of AI tools such as chatbots for sales, forecasting, functions automation are already benefiting from an increase level of efficiency.

Start with a vision for AI. An understanding up-front of what AI can do for the business is crucial. It is important for executives to understand what they are looking to change before driving into execution. Setting up goals and KPIs for a successful transformation initiative is a worthwhile exercise for business leaders. Ensuring that the team assigned to AI development is given clear directions as to which platforms and systems are to be addressed, understand the priorities for the organization and, are able to extrapolate achievable goals and value from these systems. AI is increasingly reshaping the customer experience and transforming businesses across industries. According to Gartner 37% of leaders in service organizations worldwide are piloting or using AI bots and VCAs (virtual customer assistants), 67% of those leaders believe they are high-value tools in the contact center. Senior executives we have spoken with in the Wealth Management space want to increase their investments in AI-driven technologies in order to better serve clients and for competitive advantage.

Develop a Team and Talent One of the key challenges for firms that are gearing up to tackle AI and Machine learning initiatives is that they are quickly discovering that a focus on talents is critical to achieving AI strategy. Developing a pool of talents at the onset is an important first step. A focused team is able to help drive AI initiatives from conceptualization to implementation. Most AI-driven organizations are creating the role of AI engineers and employing people who are well-versed in data engineering, data science, and software development tasks. Recently firms like Google, Microsoft have launched Online Courses in AI to enhance the skills of professionals for this area. Others have devised creative ways for acquiring talents such as hiring University professors who have taught AI to complement their teams. Working with a reputable vendor to assist AI teams or internal AI Engineers early in the process, can be beneficial. As a result, in order to undertake AI initiatives, firms must ensure that they have the right expertise within their organizations to carry out the tasks needed to realize their objectives.

AI talents and skillsets need to be developed and maintained in order to tackle future business models but, successrequires more than technology talents. Having subject-matter experts (SMEs) who are well versed in the business, understand internal operations to address the data requirements with data scientists and, who are able to communicate with executives can be beneficial. A comprehensive range of skills is needed for AI initiatives. These are to include AI researchers, AI engineers, data scientists, UX designers, Change management/transformation experts, project managers, AI-focused business leaders and SMEs. Establishing a center of excellence in AIto work in collaboration with business leaders and AI vendors is widely recommended to create the necessary technical infrastructure and, to help gain better understanding of the underlying processes needed for a successful AI strategy for customers. In a recent survey of U.S. executives using AI, 37% said they have already established such an organization. Finally, since AI talent is scarce, centralization of functions will contribute to greater focus and agility when working with various stakeholders around the organization and deploying AI projects.

How's your AI Enterprise?

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