Christian Stegh, CTO and VP of Strategy at eGroup | Enabling Technologies.
Artificial intelligence (AI) is creating new opportunities for innovation, efficiency and competitive advantage. However, many organizations are struggling to get started, let alone realize its full potential. Rightfully so. Sifting through the hype to align AI initiatives with business outcomes is not trivial.
My recent Forbes article began a series about an AI maturity model that we’re developing from my work with approximately 150 organizations in the field. This next article furthers that framework, but focuses on business alignment. The framework is based on five stages: learning, experimenting, standardizing, innovating and leading. Each stage represents a different level of adoption and business integration and outlines a different set of challenges and best practices. By following this or a similar framework, organizations can develop a clear and coherent AI strategy that supports their vision, goals and values.
The ultimate aim of this framework is to help organizations use AI not only as a technology, but as a strategic capability that drives business outcomes. Results are the only measure of AI’s success and impact. Whether it is increasing revenue, reducing costs, improving customer satisfaction or enhancing social good, AI should always be aligned with the desired outcomes of the organization and its stakeholders.
Stage 1: Learning
At this point, most organizations recognize some potential for AI and are curious about how it can help them achieve their business goals. They may have some basic knowledge of AI concepts and tools, but lack the skills and experience to apply them effectively. They learn from external sources, such as vendors, consultants or peers. They may have some isolated use cases or proof-of-concepts, but they are not aligned to an overall strategy or vision.
Stage 2: Experimenting
In this stage, organizations have moved beyond curiosity and are actively experimenting with AI for specific business purposes. They are looking for ways to improve efficiency, reduce costs or enhance customer experience with AI. They seek to prove tangible ROI and meaningful business cases for AI investments. They may have some teams or resources incubating AI, but they are not integrated with the rest of the organization.
Stage 3: Standardizing
Executives have bought in to AI and are dedicating resources and teams to drive adoption and innovation. In stage three, an organization has capabilities to implement and manage AI across the organization, in core business processes and functions. Oftentimes, AI initiatives are coordinated by a Center of Excellence. Org-wide processes are regularly updated yet lack alignment across departments.
Stage 4: Innovating
In this stage, organizations have leveraged AI to create new value propositions and competitive advantages. They have enhanced their products, services or business models with AI features or functionalities. They have identified and exploited new opportunities or markets with AI. They have fostered a culture of experimentation and agility, where they can quickly test and iterate on new ideas. Cross-functional processes are documented, verified and improved regularly.
Stage 5: Leading
In rare circumstances, some will become leaders in their industry or domain, setting the trends for using AI. They will augment or even redefine their mission with AI at the core. They’ll possess a sustainable competitive edge with AI that is hard to replicate or surpass.
Auspicious goals, to be sure, but at this point, don’t the possibilities seem endless?
Conclusion
AI success is not a linear path for all, but a journey through different levels of alignment, investment and innovation. Organizations who intentionally align priorities and investments to business goals stand to excel.
No matter what stage they are in, organizations can always learn from others who have gone through similar experiences and seek guidance from experts who can help accelerate progress.
AI is not a destination, but a continuous process of learning, experimenting, standardizing, innovating and, eventually, leading.
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