Launch Your AI Proof of Concept

Technology leaders need to assess the technical feasibility and the business value of AI initiatives before they make a significant investment.
They need to show not only that AI use cases can work as intended but also that they will yield tangible business benefits to secure support for a larger pilot or implementation.
Leaders face time constraints to demonstrate the viability and benefits of AI use cases. If the assessment takes too long, it could lead to funding delays or missed opportunities.

Our Advice

Critical Insight

Identify relevant capabilities to support your AI use case, and streamline your vendor selection process to find the right implementation partner.

Impact and Result

Identify relevant capabilities to support the AI use cases you identified.
Validate AI use cases against business requirements.
Identify vendors to support AI use cases, devise a vendor selection model, and select products for review.

Launch Your AI Proof of Concept Research & Tools

1. Launch Your AI Proof of Concept Deck – A step-by-step guide that walks you through how to select vendors to support your AI use case.

Use this storyboard to identify relevant capabilities to support your AI use case, validate AI use cases against business requirements and identify vendors to support it.

2. AI Proof of Concept Workbook – A workbook to guide IT leaders and practitioners as they scope, evaluate, and plan a proof of value for an AI initiative within their organization.

Use this tool to scope, evaluate, and plan a proof of concept for your AI initiative.

3. Vendor Selection Tools – Two Excel tools that structure the vendor data collection and selection process, and an AI Vendor Interview Script to help you make the most of AI vendor conversations.

Use the AI Vendor Self-Analysis Tool to structure the data you collect from prospective vendors.

Use the AI Vendor Analysis Tool to devise a vendor selection model and identify vendors to support AI use cases.

Use the AI Vendor Interview Script to structure vendor conversations.

4. Workshop Summary – A customized deliverable that captures analysis, decisions, and next steps identified during the workshop for your key stakeholders.

Use the AI Proof of Concept Workshop Summary to capture the outcome of the project, including data collection and analysis, and vendor selection processes.

Workshop: Launch Your AI Proof of Concept

Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.

Module 1: Explore the Relevant AI Market

The Purpose

Validate the AI use case and explore relevant vendors.

Key Benefits Achieved

Identify relevant AI capabilities and create a list of relevant vendors and products.

Activities

Outputs

1.1

Validate use case.

AI pilot use case scope

1.2

Validate success criteria.

Validated success criteria

1.3

Identify AI marketplace capabilities and trends.

Alignment on vendor category and longlist of vendors for consideration

1.4

Evaluate existing technology stack.

Initial system design for AI use case

Module 2: Gather Requirements

The Purpose

Gather accurate requirements based on your vendor assessment and vendor category review.

Key Benefits Achieved

Identify and prioritize essential features.

Activities

Outputs

2.1

Identify and prioritize requirements.

List of prioritized requirements that satisfies the given use case

2.2

Compare vendor features and capabilities.

Validation of use case coverage across different vendors

2.3

Draft a vendor shortlist.

A vendor shortlist based on capabilities and use case coverage

Module 3: Evaluate Vendors

The Purpose

Perform vendor interviews to select the right partner for your proof of value initiative.

Key Benefits Achieved

You have selected a vendor that meets your requirements.

Activities

Outputs

3.1

Create a vendor selection model.

A vendor selection model to be used to evaluate vendor shortlist

3.2

Build interview scripts.

Interview script to ensure reliability and consistency during the interview process

3.3

Post-workshop: Conduct vendor interviews.

(Post-workshop) Completed vendor interviews

3.4

Validate technical issues.

Known list of technical considerations

Module 4: Prepare Implementation

The Purpose

Validate implementation activities against internal capabilities.

Key Benefits Achieved

A validated implementation plan that can be executed by your team.

Activities

Outputs

4.1

Determine the internal capabilities needed to execute your proof of value.

List of internal capabilities required to execute the proof-of-value pilot

4.2

Review implementation activities.

A validated list of implementation activities to leverage during the pilot

Launch Your AI Proof of Value

Launch Your AI Proof of Concept

Accelerate your implementation.

WORKSHOP OVERVIEW

Analyst perspective

Look before you leap.

The first goal of a proof of concept (PoC) is to determine the technical feasibility of your AI use case. An AI PoC aims to answer whether the technology can work in a real-world environment, identify technical and integration challenges, and mitigate risks before proceeding to a larger-scale implementation.

In contrast, a proof of value (PoV) focuses on demonstrating the broader business value and benefits of the technology. An AI PoV aims to answer whether the technology can deliver tangible benefits, such as cost savings, efficiency improvements, or revenue increases. A successful PoV will show not only whether the technology can perform the intended functions, but also whether it will achieve specific business outcomes.

PoVs are more resource intensive than PoCs, but the deeper exploration of the technology's impact on the business is well worth the effort. Determine whether the AI use cases under consideration can work as intended, but don’t forget to assess their business value as well before committing to a full-scale implementation.

Michel Hébert
Principal Research Director, Security and Privacy
Info-Tech Research Group

Executive summary

Your challenge	Common obstacles	Info-Tech’s approach
Technology leaders need to assess the technical feasibility and the business value of AI initiatives before they make a significant investment. They need to show not only that AI use cases can work as intended but also that they will yield tangible business benefits to secure support for a larger pilot or implementation. Leaders face time constraints to demonstrate the viability and benefits of AI use cases. If the assessment takes too long, it could lead to funding delays or missed opportunities.	Leaders struggle to define relevant use cases effectively, validate AI use cases against business requirements, and find the right vendor to support them. Organizations lack AI expertise, which can make it difficult to conduct meaningful assessments. AI use case assessments are smaller in scale than full implementations, but they still involve licensing, hardware, and personnel costs. Managing limited budgets well is essential.	Identify relevant capabilities to support the AI use cases you identified. Validate AI use cases against business requirements. Identify vendors to support AI use cases, devise a vendor selection model, and select products for review.

Info-Tech Insight

Streamline your vendor selection process to identify relevant capabilities to support your AI use case and find the right implementation partner.

Your challenge

You need to evaluate the feasibility and value of AI initiatives.

Technology leaders need to assess the technical feasibility and the business value of AI initiatives before they make a significant investment.
Proofs of concept are only a part of the equation. Leaders need to show not only that AI initiatives can work as intended, but also that they will yield tangible business benefits.
Feasibility and value assessments face significant time constraints. If the project team takes too long to secure support for a larger pilot or implementation, it could lead to funding delays or missed opportunities.
Assess if the technology selection and enablement were “done right” with positioning proof of value first in your organization.
Build organizational “AI muscle” before leaping into a full deployment at scale.

Common obstacles

Finding suitable vendors can be difficult without industry expertise and standards.

Leaders struggle to define relevant use cases effectively, validate AI use cases against business requirements, and find the right vendor to support them.
AI use case assessments are smaller in scale than full implementations, but they still involve licensing, hardware, and personnel costs. Managing limited budgets well is essential.
Meanwhile, organizations lack AI expertise to assess the explosion of potential use cases. Without established standards or reliable data, it can be difficult to conduct meaningful vendor selection.
As always, subjective vendor content marketing and slick sales presentations can obscure the real capabilities of the product.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

Table of Contents

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Get the help you need in this 3-phase advisory process. You'll receive 7 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Scoping

Call 1: Discuss your specific challenges.
Call 2: Review workshop structure.
Call 3: Scope workshop engagement.

Guided Implementation 2: Prework

Call 1: Prepare preworkshop activities.
Call 2: Review outcomes and finalize engagement logistics.

Guided Implementation 3: Engagement and next steps

Call 1: Review engagement deliverables and discuss next steps.
Call 2: Access advisory, technical services, and consulting to discuss vendor interviews and plan next steps.