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Business Value: The #1 Barrier to AI?

Gartner Number One AI Barrier is Business Value

Amidst the prevailing hype, extensive evaluations, and proof-of-concept endeavors, AI is encountering several barriers that are slowing mainstream adoption and growth, with the number one issue being a lack of Business Value Clarity.

Gartner, in its study encompassing nearly 700 enterprise tech leaders, delved into the potential obstacles impeding AI’s widespread integration. While conventional wisdom might suggest concerns such as data governance / security or skills shortage to be predominant, Gartner’s findings reveal that IT leaders struggle with gauging the Business Value derived from their AI initiatives. There exists a notable deficit in comprehending the practical applications of AI and resulting tangible business benefits.

According to Gartner, “The principal hurdles to AI implementation revolve around the challenge of comprehending the benefits and applications of AI techniques, coupled with the complexity of quantifying AI’s value. As enterprises transition from experimental phases to real-world AI deployment at scale, the imperative lies in extracting tangible value from AI. However, conventional methodologies for assessing and realizing AI’s value fall short.”

For AI commercial leaders, acknowledging and actively addressing the barrier of business value is pivotal for ensuring the success of AI endeavors. This entails:

Marketing Leaders:

  • Clearly outlining prescriptive use cases tailored to specific industries, segments, and functions.
  • Articulating the potential business value outcomes achievable through the utilization of AI solutions.
  • Presenting concrete examples of successful business value realization, supported by quantifiable outcomes rather than mere anecdotes.

Sales and Enablement Leaders:

  • Empowering sales teams to engage collaboratively with prospects to identify use case opportunities.
  • Developing frameworks and content to facilitate the discovery of AI opportunities and prescribe use cases, along with modeling quantifiable business value outcomes for each unique scenario.
  • Providing value automation tools to assist sales representatives and consultants in constructing the financial justification for each use case dynamically.

Customer Success Leaders:

  • Driving sustained customer engagement and expanded adoption by jointly quantifying the realized value from existing AI initiatives.
  • Proactively exploring additional AI applications with each customer, quantifying the value of these proposed use cases.
  • Curating customer case studies and benchmarks showcasing business value enhancements, and disseminating them to marketing, sales, and customers to elucidate the achievable ROI in real-world applications.

What Metrics Matter?

Regarding the metrics leveraged by buyers who successfully identify the business value of AI, Gartner highlights:

  • Customer Success: Enhancing the customer experience.
  • Cost Efficiencies: Boosting productivity, streamlining processes, and minimizing or circumventing expenses.
  • Business Growth: Identifying and capitalizing on growth opportunities.

These metrics, while not drastically different from those employed for other solutions, underscore the necessity for a proactive stance from commercial teams, particularly in delineating clearer use cases, substantiating value propositions, and outlining roadmaps.

The Bottom-Line

Solution providers offering or integrating AI solutions stand on the brink of remarkable revenue growth potential, given the pronounced customer interest and demand. However, the lack of AI business value clarity is the number one barrier to your success.

The most successful providers will be those who adeptly navigate the transition from initial hype to widespread adoption, proactively tackling the foremost barriers, notably the Business Value gap.

To surmount this gap and provide effective business value guidance to AI customers, concerted efforts are imperative. As an AI commercial leader, analyzing existing customer successes to ascertain the actual value realized serves as a foundational step. For prospects and expansions, elucidating use cases, prescribing a coherent starting point, and crafting a sequential roadmap over time, while assembling the pertinent business value components, emerge as indispensable strategies. 

How are you proactively providing AI business value clarity for your prospects and customers?


Checkout ways to improve value clarity and articulation here.



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