From concept to impact: 10 steps for AI value-creation
Written by Kristofer Kaltea & Jens Eriksvik
Businesses are realizing that proving AI can work is no longer enough. To succeed, AI initiatives must deliver measurable value and remain adaptable to long-term needs. The shift from proof of concept (PoC) to proof of value (PoV) represents a fundamental change—one that emphasizes outcomes over feasibility and ensures AI solutions address real business challenges.
At Algorithma, we go beyond PoV with a focus on proof of sustainability (PoS). Our use-case-driven approach ensures AI projects deliver actionable results today while building a foundation for lasting impact. By targeting specific, high-value problems and embedding AI into core business functions, we help clients transition from isolated experiments to sustained transformation.
From feasibility to value
Traditional PoCs addressed one question: can this technology work? While this was useful in AI’s early days, it often led to solutions that failed to scale or deliver real business benefits. PoCs frequently focused on technology for its own sake, neglecting alignment with business objectives.
PoV reframes the conversation, asking:
What value does this solution bring to the business?
How does it support strategic goals?
Can it scale effectively to meet future needs?
This approach ensures AI initiatives are both technically feasible and strategically aligned, creating measurable outcomes that justify further investment. At Algorithma, this principle underpins our use-case-driven methodology. By identifying specific, high-impact problems, we design solutions that not only deliver results but avoid the pitfalls of siloed implementations.
“The true power of AI lies not in proving its feasibility, but in its ability to solve real-world challenges, deliver measurable outcomes, and sustain value over time. By aligning AI initiatives with strategic goals and embedding them into core business processes, organizations can move beyond experimentation to drive lasting transformation.”
- Jens Eriksvik, CEO
Use-cases: The foundation of PoV success
For AI to drive meaningful outcomes, it must address real-world problems. Use cases provide the structure to bridge high-level strategy with actionable execution, ensuring solutions are grounded in business needs rather than technological experimentation.
For example, a financial services company facing slow loan approvals implemented AI-powered document review. This reduced approval times, improved customer satisfaction, and streamlined operations. Similarly, a client looking to improve operational efficiency worked with cross-functional teams to identify AI opportunities. By aligning use cases with strategic priorities, they ensured their efforts delivered measurable and scalable value.
However, identifying the right problem is only the first step. Success depends on defining clear goals, achieving measurable outcomes, and building a foundation for scalability.
Building momentum: pain points, metrics, and scalability
These principles ensure AI projects are targeted, measurable, and scalable. They address immediate challenges while laying the groundwork for future expansion.
The next step: Proof of (value) sustainability
Delivering value is important, but sustaining it over time is essential for meaningful transformation. Proof of sustainability (PoS) ensures that AI solutions remain adaptable, relevant, and aligned with evolving business priorities.
AI sustainment is about embedding continuous improvement into the lifecycle of AI systems. Feedback loops allow models to learn from new data and refine performance. Dedicated teams manage these systems, ensuring reliability and responsiveness to shifting needs. Governance frameworks maintain ethical alignment and regulatory compliance, building trust and accountability.
For instance, a manufacturing firm using AI for predictive maintenance ensures sustainability by continuously refining its system with new machine data. Governance processes align AI efforts with sustainability goals, while regular updates enhance reliability and extend equipment lifespan.
Sustainment transforms AI from a short-term solution into a long-term strategic asset. At Algorithma, our AI sustainment services go beyond maintenance. We focus on optimizing, scaling, and aligning AI systems with strategic goals to deliver continuous value. From proactive monitoring to model lifecycle management, we ensure that AI remains a driver of innovation and operational excellence.
A 10-step roadmap for transitioning from PoC to PoV to PoS
Transitioning from PoC to PoV and eventually to PoS requires a thought-through approach. From redefining value to embedding sustainability, these steps focus on actionable strategies shifts AI from isolated experiments into lasting assets.
Shift focus from feasibility to value
Move beyond technical proof to delivering measurable business outcomes. Evaluate AI initiatives based on their alignment with strategic goals and their ability to drive tangible impact.Identify specific, high-impact use cases
Focus on real-world challenges that hinder efficiency or growth. Use cases should target critical pain points and create meaningful opportunities for improvement.Define success metrics
Establish clear, measurable goals tied to business objectives. Metrics such as cost savings, revenue growth, or customer satisfaction provide benchmarks for evaluating success.Start small and iterate
Launch small-scale pilots to minimize risk and refine the approach. Use insights from pilots to validate assumptions and prepare for broader implementation.Scale effectively
Leverage lessons learned from pilots to scale solutions across the organization. Design systems with scalability in mind to ensure seamless expansion.Build a framework for sustainability
Develop structures for managing AI systems over the long term. This includes governance policies, dedicated sustainment teams, and integration into daily operations.Embed feedback loops
Continuously collect data and monitor performance to refine models and adapt to changing needs. Feedback ensures systems remain effective and relevant.Align with ethical and regulatory standards
Implement governance frameworks to maintain compliance and uphold ethical AI practices. Regular audits and oversight ensure trust and accountability.Create a culture of continuous improvement
Foster ongoing learning and innovation across teams. Equip employees with the skills and knowledge to adapt and evolve AI systems as the organization grows.Regularly revisit priorities and performance
Schedule periodic reviews to assess the impact of AI initiatives. Reevaluate use cases, metrics, and goals to ensure alignment with evolving business needs.
Transitioning from PoC to PoV to PoS transforms AI from a technical trial to a strategic asset. By focusing on high-impact use cases, aligning with strategic goals, and defining clear success metrics, organizations ensure measurable outcomes. Pilots allow testing and refinement before scaling solutions effectively.
Sustainability ensures long-term impact through governance, feedback loops, and continuous improvement, keeping AI adaptable and aligned with evolving needs. This roadmap establishes AI as a driver of lasting transformation and competitive advantage.
“In my experience, the hardest part of AI isn’t the technology—it’s figuring out where to start. The right use cases make all the difference. When you focus on real problems that matter to the business, AI stops being an experiment and starts driving meaningful, lasting change.”
- Kristofer Kaltea, Business Operations leader
From proving feasibility to sustaining impact
The transition from PoC to PoV to PoS marks a fundamental shift in how organizations adopt and leverage AI. By targeting high-impact use cases, defining clear success metrics, and scaling effectively, businesses move beyond experimentation to deliver measurable strategic outcomes. Sustainability is key—embedding AI into core operations, fostering adaptability, and ensuring alignment with ethical and strategic goals unlocks AI’s long-term potential.
At Algorithma, we guide clients through this entire journey. Our use-case-driven methodology and focus on value delivery and sustainability ensure AI solutions are impactful today and transformative for the future. As AI continues to evolve, businesses that master this shift will set the standard for innovation, operational excellence, and sustained growth.
