AI Strategy - Yes, You Need One
What is your Artificial Intelligence (AI) strategy? Do you – or your organization – have one, or have you considered the need for one? If not, now is the time to develop and implement that strategy. In this article, we will cover some of the key components your AI strategy needs to address.
What Is An AI Strategy?
At a high level, an AI strategy defines how your organization will use AI, the specific AI tools that team members are authorized to use, polices and procedures for using AI, and impermissible uses of the Company’s AI platforms and services. Your AI strategy should address numerous items, including:
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- Your organization’s vision and objectives for using AI
- Samples of use cases
- The AI tech stack
- Ethics and compliance issues
- Developing AI skills
- How to implement AI in the organization
- Measuring success
Why You Need An AI Strategy
For many, perhaps most, organizations, AI is no longer optional. Instead, it is a competitive necessity. Failing to leverage AI could jeopardize an organization’s ability to meet its strategic, operational, and financial objectives. Yet, at the same time, allowing team members to self-deploy AI can be a recipe for technological disaster on several fronts, including data privacy and security, copyright infringement, reliance on incorrect data, and wasting resources on unused and/or duplicate subscriptions.
Indeed, companies that recognize the need to use AI are taking a strategic step in the right direction. However, like many other technologies, it is crucial to plan, define, and document your AI strategy in detail. Then, when all stakeholders understand the strategy, execute the plan as it is defined.
As an analogy, suppose your organization is considering implementing a new accounting or ERP solution. In that case, team members would likely be brought together to develop an implementation plan for the new technology. Among the key points in that plan would likely be:
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- Creating a team of stakeholders to help select the new platform;
- Training team members on the new platform; and
- Establishing appropriate user rights and privileges to control who has access to the tools.
Why should implementing AI solutions be any different? For example, to fully leverage AI, wouldn’t it be wise to get the input of numerous stakeholders on which solution(s) best satisfy their needs? Similarly, don’t the team members who will be using the platform(s) deserve to be trained on how to use the system(s) effectively? Should we not implement appropriate security measures to prevent unauthorized users from accessing the system? Furthermore, and on a related note, should the organization not create a policy that instructs team members not to use unauthorized AI platforms, as these platforms may not offer adequate data security and privacy controls?
Ten Key Components Of An AI Strategy
Based on the discussion above, it should be clear that selecting and implementing AI in an organization is not merely a matter of signing up for a subscription to a tool like ChatGPT, Gemini, or Copilot. Instead, it should be a concerted effort among numerous stakeholders to maximize the likelihood of a successful implementation. To that end, the following are ten key components of a successful AI strategy.
- Clearly define why AI is now a business necessity in your organization. Ensure that stakeholders understand the value of AI and secure support from senior leadership support for the AI project.
- Ensure that your anticipated AI use aligns and conforms with various legal, ethical, and regulatory standards and requirements.
- Define priorities for which divisions, departments, and users provide the most promise for immediate and measurable outcomes, and concentrate resources on these groups first.
- Select and implement the “right” AI platforms, based on team members’ needs.
- As mentioned earlier, train team members on the proper use of the AI tools that are provisioned to them.
- Implement pilot programs with a small number of users before rolling out AI to a larger audience.
- Ensure that your AI strategy addresses appropriate data governance, integrity, access, privacy, and security objectives.
- Identify and incorporate appropriate metrics to measure AI’s Return on Investment (ROI). For example, one key metric might be to measure the amount of time team members save each week as a result of the AI initiative. Track these metrics and, when possible, apply “dollars-and-cents” values to them.
- Ensure that vendors and partners are thoroughly vetted and evaluated before engaging. Verify that you are licensing a trusted and tested technology, not the promise of one.
- Recognize that AI, like almost all technology, changes rapidly. Therefore, you will likely need to revise your AI strategy periodically, especially in the first year. Plan accordingly and don’t hesitate to make adjustments when necessary.
Summary
AI is here to stay – and thankfully so! The productivity and efficiency gains offered by AI are unmatched by any previous technology. Even more exciting is the fact that AI is still in its infancy, which likely means that these gains will only continue to multiply going forward. However, organizations that fail to create and implement an effective AI strategy will likely not realize the ROI that they could and should through AI. Thus, be sure to develop an AI strategy and ensure that all team members are aware of it and trained to use AI in an ethical and responsible manner, so that your organization can reap the benefits of AI.
