Build Your AI Strategy Roadmap

Develop your AI strategy to maximize return and mitigate risks with your AI investments.

Analyst Perspective

Transforming the organization with AI.

Today, every organization is being challenged to determine their strategy on the use of AI-based solutions. Never in our history has a technology become so accessible and, at that same time, so disruptive. This is a unique time in our history. The benefits of AI are transformative and readily accessible to all organizations – but the introduction of transformative capabilities also introduces new risks that need to be planned for.

A successful business-driven AI strategy requires:

• Alignment to the organizational strategy.
• AI goals and strategic AI principles to guide investments.
• Candidate business capabilities that can be augmented or automated with AI to drive business value.
• A roadmap to deliver and support new AI-based solutions.

Bill Wong
Research Fellow
Info-Tech Research Group

Executive Summary

Your Challenge

AI is disrupting all industries and providing opportunities for organization-wide advantages.

Organizations need to understand this disruptive technology and the trends to properly develop a strategy for leveraging this technology successfully.

C-suite technology leaders need to:

• Identify AI use cases that align with your organization’s capabilities and goals.
• Organizations need to adopt a data-driven culture.

All organizations, regardless of size, should be planning how to respond to this new and innovative technology.

Common Obstacles

Business stakeholders need to cut through the hype surrounding AI to optimize investments for leveraging this technology to drive business outcomes. They need to:

• Understand the market landscape and the benefits and risks associated with AI.
• Understand the gaps the organization needs to address to fully leverage AI.

Without a proper strategy and foundational AI guiding principles, the risks to deploying this technology could negatively impact business outcomes.

Solution

Info-Tech’s human-centric, value-based approach is a guide for deploying AI applications, including:

• Aligning AI initiatives to the organization’s business drivers.
• Adopting strategic AI guiding principles.
• Evolving an AI maturity model.
• Prioritizing candidate generative AI-based use cases.
• Developing AI policies.

This blueprint will provide a list of activities and deliverables required for the successful deployment of generative AI solutions.

Info-Tech Insight

Create awareness among the CEO and C-suite executives about the potential benefits and risks of transforming the business with AI.

Your challenge

This research is designed to help organizations that are looking to:

• Develop a business-driven AI strategy to maximize the benefits and minimize the risks associated with AI-based solutions.
• Understand the potential opportunities to improve business outcomes and best practices to govern the risks with developing or deploying AI applications.
• Assess the organization’s capabilities to provide AI governance, a data platform optimized for analytics, access to AI skills and processes, and the supporting technology infrastructure.
• Have clear metrics in place to measure the progress and success of AI initiatives.
• Build the roadmap to implement candidate use cases.

Common obstacles

These barriers are challenging for many organizations:

• Getting all the right business stakeholders together to develop the organization’s AI strategy, vision, and objectives.
• Establishing strategic AI principles to guide AI investments and deployments.
• Advancing the AI maturity of the organization to meet requirements of data and AI governance as well as human-based requirements such as fairness, transparency, and accountability.
• Assessing AI opportunities and developing policies for use.

Align your AI strategy with AI governance

An effective AI strategy must intersect with an organization’s governance and compliance requirements

Scope

• This blueprint provides guidance for aligning your AI strategy with your organizational strategy.
• This approach sets the foundations for building and applying foundational AI principles and AI policies aligned to corporate governance and key regulatory obligations (e.g. privacy). Both steps are foundational components of how you should develop, manage, and govern your AI program but are not a substitute for implementing broader AI governance.

Guidance on how to implement AI governance can be found in the blueprint linked below.

Download our Govern the Use of AI Responsibly With a Fit-for-Purpose Structure blueprint

Measure the value of this blueprint

Leverage this blueprint’s approach to ensure your AI initiatives align with and support your key business drivers

This blueprint will guide you to drive and improve business outcomes. Key business drivers will often focus on:

• Improving customer experience
• Increasing revenue
• Reducing costs
• Improving time to market
• Reducing risk

In Phase 1 of this blueprint, we will help you identify the key AI strategy initiatives that align to your organization’s goals. Value to the organization is often measured by the estimated impact on revenue, costs, time to market, or risk mitigation.

In Phase 4, we will help you develop a plan and a roadmap for addressing any gaps and introducing the relevant AI capabilities that drive value to the organization based on defined business metrics.

Once you implement your 12-month roadmap, start tracking the metrics below over the next fiscal year (Year 1) to assess the effectiveness of measures:

Example business outcome objectives and metrics for a private organization.

Build Your AI Strategy Roadmap

Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889

Info-Tech offers various levels of support to best suit your needs

Guided Implementation

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization.

A typical GI is 10 to 12 calls over the course of 2 to 3 months.

What does a typical GI on this topic look like?

Insight summary

Overarching Insight

An AI strategy cannot be derived unless the organization is clear on its forward-looking goals and objectives. An effective AI strategy must align to the organization’s strategy.

AI Strategy

A business-driven AI strategy is one that is aligned with the firm’s organizational strategy. Key components of the AI strategy include:

• AI vision and mission statements
• Business value drivers
• Strategic AI principles
• Foundational AI principles

Buy vs. Build

Most organizations will be exposed to AI via incumbent software or purchasing off-the-shelf tools. Seek to buy first before deciding if you have no other option but to build.

• Assess current AI maturity.
• Identify AI strategic investment path.

Opportunity Prioritization

Assess candidate business capabilities targeted for generative AI to see if they align to the organization’s business criteria, foundational AI guiding principles, and capabilities for delivering the project.

• Develop a prioritized list of candidate use cases.
• Detail use cases and estimate business value.

Tactical Insight

Business stakeholders need to cut through the hype surrounding AI, including apps like ChatGPT, to optimize investments for leveraging this technology to drive business outcomes.

Tactical Insight

Identify and prioritize use cases that deliver immediate operational benefits while also laying the groundwork for broader transformation.

Blueprint deliverables

Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:

AI Strategy and Roadmap Presentation Template

AI Use Case Selection Tool

AI Maturity Assessment Tool

AI Initiatives Prioritization and Roadmap Planning Tool

Our AI Maturity Assessment Tool, AI Initiatives Prioritization and Roadmap Planning Tool, and AI Strategy & Roadmap Presentation Template enable you to shape your generative AI roadmap and communicate the value of the initiatives to your C-suite sponsors.

Case Studies: Leveraging AI Strategy

Overall Impact: 9.4/10 | Average $ Saved: $55,509 | Average Days Saved: 34

City of Arlington

“We are incredibly grateful for the facilitator and the AI strategy process, which truly stood out as the most impactful part of the workshop. As a large city with over 27 lines of business, Info-Tech's AI Strategy Workshop brought our City departments together in a meaningful and transformative way, far exceeding expectations. The value it provided was unmatched by any other initiative we’ve tried in-house.”

• Impact: 10/10
• $ Saved: $137,000
• Days Saved: 90

County of San Luis Obispo

“Well organized material; knowledgeable, well effective presenter, quick turnaround and excellent follow-up on findings; practical application of workshop priorities.”

• Impact: 10/10
• $ Saved: $51,375
• Days Saved: 20

First Global Management Services, Inc.

“This was good reinforcement of the messages we've been hearing from other IT leaders, but it was delivered in a more programmatic way. It was a good discussion. This wasn't yet directed at time or cost savings, but we probably will have some cost savings just by not doing the wrong thing.”

• Impact: 10/10
• $ Saved: $13,700

PowerNet Limited

“Julianna was fantastic to work with, The Info-Tech material was very easy to work through. No bad parts.”

• Impact: 9/10
• $ Saved: $34,250
• Days Saved: 32

Cut through the marketing hype to understand AI

Definitions

• Artificial intelligence (AI) is human intelligence mimicked by machine algorithms. Example: Playing chess or Go.
• Machine learning (ML) is a subset of AI algorithms to parse data, learn from data, and then make a determination or prediction. Examples: Spam detection, preventative maintenance.
• Deep learning (DL) is a subset of ML algorithms that leverage artificial neural networks to develop relationships among the data. Examples: Image classification, facial recognition, generative AI.

What Makes AI Different

What Makes AI Perform