AI success is being limited by poor digital transformation
The success of AI is hampered by insufficient digital transformation, which necessitates rethinking processes and organizational structure to derive maximum value from the technology framework. According to a 2020 study conducted by Boston Consulting Group, 70% of digital transformation projects fall short of their objectives, even when priorities are well defined and leadership is aligned.
Factors that lead to failed digital transformation initiatives include identifying the right problems to solve that leads to design of incorrect approach and faulty transformation roadmap that act as a bottleneck for AI success, lack of an overarching data strategy that risk investing in improper tech stacks, lack of integration across verticals and units, and siloed projects that lead to duplicate efforts and wasted resources, as well as employee resistance to change. Additionally, the lack of CoEs and best practices, proper frameworks and approaches, poor execution due to lack of cross-pollination and coordination, and absence of a human-centric, digital-first culture, all these hinder success of AI initiatives.
To overcome these obstacles, enterprises must create AI systems that are interconnected across the enterprise, similar to a mesh or fabric, and implement a scalable architecture across the enterprise. This will help the company to take full advantage of the benefits AI can offer and slowly change their business for long-term growth by establishing a solid AI foundation with tools and processes that handle the complete discover-to-implementation cycle. Modular AI architectures offers flexibility and enable the customization of AI solutions to unique business requirements. Holistic AI architecture offers a comprehensive picture of the business and a deeper comprehension of how AI may be implemented in all domains. Scalable data fabric makes sure that it connects to all of the microservices or services in an organization. De-risk AI to handle reputational and performance risks. Agile AI architecture is critical for businesses that must respond rapidly to shifting market conditions and client demands. Agile methodologies have been acknowledged for their ability to enhance teamwork, eliminate silos, and empower decision-making and project management.
Like a fabric and mesh, AI must be integrated into all business areas to achieve digital transformation. This will fundamentally transform how the firm runs and provides value to customers. Businesses need to grasp digital transformation to take advantage of its opportunities by breaking down siloed procedures that prevent AI integration and powerful digital transformation
Source: Venture beat