A few days ago, I attended a virtual holiday happy hour with my best friend from college, Will, and our close mutual friend, Erin. Erin is a seasoned public relations veteran and communications professor and I often invite her to my classes at the University of Oregon as a guest speaker. As we toasted the holidays, the conversation turned to AI and its impact on the new year.
My friends told me that I was one of the only professionals in their network who had a positive outlook on AI and had embraced its use at work. I was pleasantly surprised to learn that I offered a unique perspective and happily shared the many ways I had used generative AI for marketing. Erin then asked me a great question, which was: “How are you starting to introduce such a disruptive tool into an organization? »
So — Erin and Will, my loves — this article is for you and anyone looking to be an AI champion at work. This article will help you:
- Better understand how AI can help you and your team.
- Build a basic AI strategy.
- Integrate generative AI into your organization.
However, this article is not:
- A risk assessment analysis.
- Legal advice on how to manage risks.
- Governance strategies or safeguards.
- A list of the best AI tools (they will change over time).
There are excellent resources available on these important topics, including National Institute of Standards and Technology AI Risk Management Frameworka great place to start if your role is responsible for AI governance.
Building a Core AI Strategy
As with any project I undertake, whether personal or professional, I always start with strategy. The basic elements of an effective strategy are an overall objective; a target audience and audience profiles; budget; and KPIs to help you measure the results of your strategic planning. So let’s start with these three fundamental questions:
- Identify the opportunity and objective: What marketing tasks could benefit from help from AI tools?
- Identify your target user base: Which roles within my organization perform these tasks?
- Define KPIs: How will we measure the success of our AI tools to positively impact the accomplishment of these tasks?
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Identify the opportunity
This first step involves identifying specific marketing areas and tasks that would benefit from generative AI. This includes evaluating content creation, data analysis, customer engagement, and campaign optimization tasks. I recommend a good old-fashioned brainstorming session, where you list all the tasks that are currently part of your team’s workflow. You may want to review previous articles in my Decoding AI for Marketing seriesbecause they are full of creative marketing applications for generative AI tools.
For additional inspiration, I designed a blog post and an infographic that lists seven marketing categories or pillars and the specific marketing tasks associated with each that can benefit from AI.
The pillars include:
- Content creation and management.
- Data analysis and information.
- Engagement and customer experience.
- Campaign optimization and management.
- Marketing and product strategy.
- Digital marketing and e-commerce.
- Event marketing and public relations.
Target users
Once you have identified the specific tasks and goals of your AI strategy, you can then work to identify the roles within your organization that will need access to AI tools. Depending on the size of your business, your marketing department may have hundreds or even thousands of people managing very specific tactics. As one of my colleagues at Intel liked to say, we must not “boil the ocean”. A small pilot group focused on a specific area would therefore be a good starting point.
If you work for a startup or SMB, your marketing team will likely be small and agile, with just a handful of roles dedicated to many marketing channels. Identifying key contributors responsible for the tasks you identified in Step 1 who are willing and able to evaluate these new tools will help ensure the success of your plan.
You may also want to conduct a skills gap analysis, assessing the team’s current skill levels in AI technology and identifying areas where training or recruitment may be needed.
KPIs for your AI toolset
The next step in this basic strategic planning process is to determine how you will measure the results and performance of your AI toolset. These metrics will be specific to the tasks you have identified and could help measure increased productivity, creativity, work quality, customer engagement, and many other potential outcomes.
The most important ingredient of this step is for all stakeholders to align on the metrics that will determine the effectiveness of AI-based outcomes.
Budget and human resources
Determining the budget, time and human resources needed to implement your AI is an essential part of the planning process. This includes software costs, training expenses, and potential hiring. I recommend starting with a small pilot project, proving the ROI of a small initial investment, and then scaling it up more broadly across the organization.
To help you organize the outcome of this basic strategy, I have developed a AI Strategy Worksheet or a template, which you can use as a collaboration tool when brainstorming with your team. I recommend loading this in Miroan interactive whiteboard tool, allowing remote teams to create ideas together and easily record everyone’s contributions.
Next steps
Building this basic AI strategy will prepare you and your team for a successful AI implementation. Stay tuned for additional articles in the Decoding AI series which discuss more details on these next steps:
- Building an AI toolbox – tool selection
- AI communications and education – training and adoption
- KPIs and results measurement
As always, I am available for any questions or help you may need in integrating this into your organization.
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The opinions expressed in this article are those of the guest author and not necessarily of MarTech. Staff authors are listed here.