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3 Things You Need to Know for a Successful AI Implementation

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“It is not possible to prove any new thought, concept, or idea in advance. All new ideas can be validated only through the unfolding of future events.”  —Charles Sanders Pierce

AI represents a tremendous opportunity for any business in regards to growth, customer acquisition, and customer success. Although, what matters most is the implementation. Technology is not a solution, it's an enabler and an accelerator. Your business process drives your technology. If the implementation phase is not done effectively, companies end up wasting more time and money than expected.

So, how do we implement AI tech the right way? It’s all about understanding the most common mistakes, learning how to avoid them, and using milestones to help you build your roadmap to success. The secret is to iterate, learn, and improve continuously. Keep reading to uncover the three critical success factors for successful AI tech implementation. 

These insights came from The 5 Critical Success Factors for AI Implementation, an AI Academy for Marketers course presented by Doug Davidoff (@dougdavidoff) of Imagine Business Development

Learn more about AI Academy below. 

1. Map Out Clear, Solid Business Processes

The first step to unlock the power of AI is to unlock your business process. Fundamentally, if you don’t have a strong existing framework, you will not unlock your desired results. The difference between successful AI implementations and those that don’t hit their mark is the clarity of what the AI is supposed to do and how it is going to happen. 

A good starting point is to map out your process. By doing this, we mean:

  • Define the process, and find the key inflection points.
  • Identify what parts of the process matter, and which do not.

After doing this, you’ll find that you have 5-7 critical inflection points. If you can accelerate these points, the ROI becomes unlocked. If you don’t map out the process, you’ll never know if what's working (or not working) is situational or design.

2. Define the Behaviors You Want to Change

Understanding the behavior side of technology is crucial to your success with AI implementation. Start your project with the end in mind and ask yourself, “What does success look like within this project?”

For the inflection points identified from the previous section, ask yourself:

  • What behaviors must change for success?
  • What behavior are you going to focus on?

Before asking yourself these questions, we recommend creating a behavior statement. The framework of a behavior statement looks something like this:

When [target group] wants to [intent] and they [situation], they will [desired behavior] as measured by [data].

Now, applying it to a real life situation could look something like this:

When a salesperson wants to identify who to contact and they go to their phone, the CRM will save them time as measured by quality call rate per hour outreach. 

After creating these behavior statements, it will be easier for you and your team to acknowledge where the focus needs to be and how you will get there. 

3. Start Small with Design Thinking

Big journeys begin with small steps. Technology goes wrong when you miss these small steps and rush to get to that finish line. If you can’t write it down clearly, map it out, or put it in a spreadsheet, you can’t automate it and the function is not ready for technology to be the enabler.

When you start this journey, you’ll need to adopt three types of design thinking to establish a successful implementation. 

Analytical Thinking 

Analytical thinking means all proof emanates from the past. You must be able to define problems and use key information to develop a solution. This is great for process optimization, and it helps to set the base for the next type of design thinking: intuitive thinking.

Intuitive Thinking

What have we learned from the past that allows us to see what is possible in the future? This is the knowing without reasoning. Intuitive thinking can help you think ahead by trusting your internal instincts. This is where things become heuristic for yourself and your team.

Abductive Logic

This is based on creating and testing hypotheses. Abductive logic brings together analytical and intuitive thinking, allowing us to establish a hypothesis to create a simple behavioral statement.

Learn More About AI Academy for Marketers Today

These insights came from The 5 Critical Success Factors for AI Implementation, an AI Academy for Marketers course presented by Doug Davidoff (@dougdavidoff) of Imagine Business Development

AI Academy for Marketers is our members-only online education platform and community. The Academy features dozens of on-demand courses and certifications taught by leading AI and marketing experts.

The courses are complemented by additional exclusive content, including:

  • Live monthly Ask Me Anything sessions with instructors. 
  • The Answering AI series of quick-take videos that provides simple answers to common AI questions.
  • Keynote presentations from the Marketing AI Conference (MAICON).
  • AI Tech Showcase product demos from leading AI-powered vendors.

Individual and team licenses are available. Discounts are offered for students, educators and nonprofits.

Ready to discover these and other important AI concepts? Sign up for the AI Academy below.

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