January 27, 2023

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AI has made headlines and will continue to do so. Most of these are quite sensational; AI becomes conscious; AI-generated art wins a contest; AI can now compose music (and more). However, what rarely makes headlines is how transformational AI can be when it comes to business, specifically how AI can help brands connect with their customers without becoming a flashy sci-fi headline.

Due to the general “sci-fi” perception of AI, many business leaders have not given serious thought to how to apply it to their business outside of data analytics or advanced research labs. And once they’ve decided to dip their toe into AI, they don’t really know where to start. Doing too much too soon is never the answer — instead, companies should take a “think global, act local” approach.

What exactly does this mean? Thinking globally means examining the impact of an AI implementation holistically and considering the company’s broader vision and objectives. When it comes to implementing AI, you have to to trade local, focusing on one small project at a time with the goal of eventually scaling up and out. But what does this look like in real life? Here are some considerations as you start your AI journey.

Determine your global goals

The first step to kickstart an AI deployment strategy is identifying those big “global” goals and needs. This will look different per organization. Some start from scratch and need to find a way to connect better with customers. Some may already have a few AI tools and want to reframe their martech/adtech strategy with the disappearance of third-party cookies in the offing. In addition, with an approaching recession, customer needs are about to change dramatically. Many companies may be moving from a customer acquisition to a customer retention model.


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This is not a one-size-fits-all approach, and acknowledging that is half the battle. While most, if not all, companies agree that customer retention is a top goal, not every organization can approach it the same way. To define your global approach, consider the needs of all stakeholders while ensuring that your systems are optimized for maximum customer benefit. And while it sounds like a major transformation, starting small can dramatically improve existing practices and technologies and transform them into continuously successful customer engagement.

Local implementation of smaller projects

Once you’ve defined your bigger goals, it’s important to redirect your thinking to acting locally. For example, if your global goal is customer retention, a local action could be deploying AI capabilities that integrate with your existing customer data platform to ensure you maximize your own data. This doesn’t require tearing and replacing, but rather an improvement on what you already have.

Using AI to better organize and activate existing customer data can improve marketing strategies, such as when and where to engage with your customers based on their exact context at a given point in time. Ultimately, this improves your customer’s experience with the brand, but organizations can also take friction out of the employee experience by taking the guesswork out of customer interactions. When customer-facing employees have instant access to data to inform jobs, their jobs become easier and they can be more successful over time. This is good for the brand outwardly and internal.

Essential AI strategy: knowing when to scale

Once the AI ​​project has proven its worth, it’s time to scale. Consider whether you would benefit most from scaling up or down your AI capabilities. If you’ve applied AI to gain more insight into a specific customer dataset, it might be time to extend that to the rest of your data. Or maybe it’s a matter of implementing an AI decision hub that can pull information from all parts of your customer-facing business to understand the full scope of the customer journey – from sales to marketing, to customer service and beyond. Either way, this is definitely a marathon, not a sprint, and companies that will benefit most from an AI deployment strategy are those that carefully and strategically build for long-term success.

The lesson here is to evolve over time. Transformation can be overwhelming and significantly disruptive. But by going small and learning what works best for your organization, you can get a sense of what your growing needs will be and ultimately create a more robust and viable long-term growth strategy.

Tara DeZao is product marketing director for AdTech and MarTech at Pega.

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