The stages of AI implementation: the “crawl, walk, run” approach
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As AI grows more and more powerful and ubiquitous, it penetrates new spheres of the human experience.
It has come to the point where virtually every industry has AI inserted into it.
But not every business has taken the step yet. Perhaps out of tradition. Perhaps out of fear. Or perhaps because they’re not sure how to make the transition.
If you’re in this last category, stick around, you might find this useful.
Keep reading to learn all about the "crawl, walk, run" method to incrementally integrate AI solutions into your workflows.
Crawl: start small, think big
The first phase involves small, slow steps but not without thinking strategically about long-term goals.
The emphasis is on identifying specific pain points or inefficiencies that AI can address. The most urgent and most automatable issues your company is facing.
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Tasks like data entry, basic customer queries, or routine analytical processes.
Through this initial stage of introspection and careful implementation of necessary solutions, you can free up valuable human resources and lay the groundwork for more sophisticated AI applications down the line.
How to crawl:
- Pinpoint areas where AI can provide immediate efficiency gains or cost savings, the low-hanging fruit.
- Launch small-scale AI initiatives (or pilot projects) to test feasibility and demonstrate tangible benefits.
- Involve employees in the process to build confidence, gather insights for future stages, and engage them from the get-go.
Walk: expand and refine
As you gain confidence and familiarity with AI, you can begin to expand its use.
More departments. More functions. More optimization.
This phase usually means scaling successful pilot projects and refining AI algorithms based on real-world feedback.
In other words, studying how your first approaches to AI landed with your audience, and what they did for your efficiency. If they were a success, finding new opportunities awaiting AI automation.
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AI-driven predictive analytics for inventory management. Personalized marketing campaigns based on customers’ behavior data. Enhanced forecasting accuracy.
This stage is all about exploration.
How to walk:
- Consolidate data sources and create databases to fuel more sophisticated AI applications and achieve an accurate understanding of your audience.
- Foster collaboration between IT, marketing, operations, and customer service teams to leverage AI from all areas.
- Regularly assess your AI’s performance, and make sure your iterations reflect your new business needs and technological advancements.
Run: achieve strategic differentiation
In this final phase, you’ll leverage AI as a core component of your competitive strategy. A key tool to driving innovation and achieving differentiation within your industry.
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AI will be embedded deeply into your processes. Predictive insights. Hyper-personalized customer experiences. Proactive decision-making. And more.
You will be able to deploy AI-powered chatbots capable of natural language processing for seamless customer support. You could implement dynamic pricing models that respond to the market in real time. The options are endless.
How to run:
- Craft a long-term AI roadmap that aligns with your business objectives and market trends. Where do you want to go and how can AI help?
- Ensure your use of AI sticks to ethical guidelines and regulatory requirements. You’re playing in the big leagues now, be responsible
- Invest in upskilling employees and empowering their talents to leverage AI’s full potential.
Now, a short case study
Amazon is a text-book case of the “crawl, walk, run” approach.
It started with basic AI applications like product recommendations based on customer browsing history. This proved AI’s capability to personalize user experiences, increase engagement, and drive sales.
The groundwork was laid. As these algorithms succeeded, Amazon expanded its AI initiatives to include logistics optimization and supply chain management. AI managed to optimize warehouse management, inventory forecasting, and delivery logistics.
This allowed Amazon to streamline operations, reduce costs, and improve delivery times. In turn, customers were more satisfied and their loyalty grew.
Today, Amazon is at the forefront of AI innovation with initiatives like cashier-less stores (Amazon Go) and an AI-driven voice assistant (Alexa). They’ve grown to harness the full potential of AI to disrupt and innovate their industry and the whole world.
Taking the dive
No one expects you to become an AI master overnight. That’s the whole point.
The “crawl, walk, run” method is meant to ease you into the world of automation. You just need to take that first step.
Seek the right talent. Invest to combat your weaknesses. Ask for help from others who’ve successfully made the transition.
Before you know it, you’ll be an expert in large language models and natural language processing.
And if you’re still not convinced, check out this week’s episode of TOP CMO, where Interactions’ CMO talks everything AI!
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