Generative AI's Business Value: Insights from Gartner 💼
By Polly Barnfield, OBE, CEO of Maybe*
Generative AI (GenAI) is reshaping industries, offering transformative opportunities for productivity, innovation, and competitive differentiation. Yet, as Gartner's research highlights, many organisations struggle to realise GenAI’s full potential due to fragmented approaches, underestimated costs, and unclear value propositions. At Maybe*, we aim to bridge this gap by enabling businesses to harness AI securely and effectively—on their terms.
Understanding Generative AI’s Potential
Gartner identifies three strategic categories for GenAI use cases: defend, extend, and upend. These represent varying levels of ambition and impact:
Defend: This strategy focuses on augmenting employee productivity through tools like copilots and assistants. While these applications are easy to deploy, they primarily maintain competitive parity without significant differentiation.
Extend: Embeds GenAI into specific processes or decisions for measurable improvements in efficiency and customer experience. Examples include automated customer service interfaces or personalised sales content creation.
Upend: This initiative drives industry transformation by creating new markets, products, or business models. It is high-risk but offers strategic benefits, such as life-changing drug discoveries or revolutionary financial services.
The Challenges: Cost, Complexity, and Governance
Despite its promise, scaling GenAI initiatives can be daunting. Gartner reports that 60% of GenAI projects fail post-proof-of-concept due to inadequate data readiness, governance issues, escalating costs, or unclear business value13. Moreover, organisations often underestimate the investments required for data management, training, and business transformation—key factors in realising long-term value.
For example:
Productivity leak: Time saved by AI tools often fails to translate into measurable business outcomes without proactive management.
Cost unpredictability: Token-based pricing models for large language models (LLMs) can lead to unexpected expenses at scale.
Governance gaps: Ethical frameworks are critical but often underdeveloped in GenAI deployments.
A Framework for Realising Value
Gartner offers actionable strategies to overcome these hurdles:
1. Align AI Ambition with Business Strategy
Determine whether your organisation’s focus is on defending its position, extending processes for differentiation, or upending the industry. This clarity will guide investment priorities and risk tolerance.
2. Manage Costs Strategically
Experimentation can be inexpensive, but scaling requires robust cost assessments. Gartner recommends balancing "build" versus "buy" options:
Buy: External applications with embedded GenAI features offer faster deployment but higher recurring costs.
Build: Custom solutions leveraging open-source models provide greater control but require advanced technical expertise.
3. Measure Productivity Gains Effectively
Track how newfound productivity impacts key business metrics like customer retention or employee efficiency. For example:
Coding assistants can improve developer output by 7–15%.
Personalised sales content creation can increase deal sizes and customer retention.
4. Invest in Governance and Change Management
Successful implementations depend on strategic alignment across HR, finance, legal, and compliance teams. Gartner emphasises the importance of AI literacy and change management programs to maximise adoption and mitigate risks.
Maybe*: Simplifying AI Adoption
At Maybe*, we simplify the complexities of GenAI adoption with our secure platform that empowers businesses to create custom AI Agents tailored to their needs. Whether your goal is to defend your competitive position or transform your industry, our solution ensures:
Seamless integration with over 2,000+ tools.
Private and secure data handling.
Customisable workflows aligned with your business strategy.
Generative AI offers unparalleled opportunities—but only if businesses approach it strategically. At Maybe*, we enable organisations to unlock this potential while staying in control.
Case Studies: Realising GenAI’s Impact
Gartner highlights successful implementations across industries:
Toyota Research Institute reduced design time through AI-assisted vehicle sketches.
Ally Bank improved customer service efficiency with GenAI-powered assistants.
Carrefour launched a generative AI shopping experience that enhanced customer engagement.
These examples underscore the transformative potential of well-executed GenAI initiatives.
Your Next Step
Generative AI is not a one-size-fits-all solution—it requires intentional planning, investment, and management. Whether you’re defending your position or aiming to disrupt your industry entirely, Maybe* provides the tools to make it happen.
With Maybe*, anything is possible. We are here to help you Get Started.
