Let´s do AI

Over the past year, an increasing number of companies have approached us with a burning question: ”How can we do AI?” It’s no surprise, given the buzz surrounding AI these days. However, this buzz also brings a lot of confusion. What is AI, really? How can it be used successfully? We’re here to clear up the confusion and tackle all your question. Remember there are no stupid questions. We make the complex simple and we address things from a business perspective. Our goal isn’t to turn you into AI developers but to help you understand how AI can be applied in a business context. Today we will cover what AI is, how you can use it, what the difference is between AI before and generative AI, and what are some good examples. So, let’s go!

What is AI?

At its core, AI is about simulating human intelligence through technology. It incorporates a large amount of technologies aimed at enabling machines to learn, understand, and act. You do not need to dive deep into the mechanics of this technology to use it; instead, your focus should be on its applications within your business. Reflect on the digital revolution, like the industrial revolution’s impact on automotive and the creation of new service models like taxis, buses, and transportation services. This revolution underscored the value of innovation and new types of service, rather than the production of cars. So in short you do not need to know how a car works to build service around it, same is true here.

Picture 1: What is AI?

Focus on value

So, if we let go of the technology for a minute and focus on value. What can AI really be used for.  I like to think of it in terms of two main areas. Making better decision and creating content. Let´s review these categories to see what they include.

Picture 2: What can we use AI for?

Better decision-making: We all have a gut feeling and our friends and neighbours have opinions, but your business deserves better. At least when it comes to areas where there is a lot of data available, and you need to make critical decision. By feeding an AI model with data, it can help us detect patterns, learn from the data, and help us make better decisions. So, AI can significantly improve decision-making processes. The decisions most crucial to you will depend on your business of course. It could be optimizing pricing, inventory management, credit scoring, detecting fraud, predictive maintenance, or preventing your customers from leaving – churn. If reducing customer churn is your focus, explore our training on developing a churn model. This application of AI has long been integrated into business operations and many companies have worked with this type of AI, often referred to as Machine learning, for many years to improve their decision making.

Picture 3: Make better decisions

Creative Content Generation: So, what is the new AI? It is what we call the generative AI. It cannot do more for us than just make better decisions and learn from data, it can also DO things for us. Like create text, code, images, videos, and even music, paving the way for innovative content creation avenues. Please note it’s important to approach generative AI with responsibility, ensuring its use aligns with ethical standards and contributes positively to society, avoiding the spread of misinformation. When it comes to examples of what you can do here only your imagination will set the boundaries. Common use cases are content automation in marketing and sales processes, internal and external chatbots and code generation in IT. But as close to everything is possible make sure you address this from a value perspective. And unfortunately to really gain value outside of just using it as stand-alone products you need to automate and integrated in to your processes to gain value.

Picture 4: Create content with generative AI

Automation and integration – key for value

Automation and integration are often key to scaling AI to truly build value for your company. AI’s value is amplified not by its standalone capabilities but by how it is woven into the broader ecosystem of business operations, enhancing efficiency, decision-making, and customer experience. For instance, while building a churn model to predict which customers might leave is insightful, the real challenge lies in acting on this prediction effectively. Similarly, on the generative side, merely accessing tools isn’t sufficient. Success centers on the seamless integration of these tools and the output into your processes, which enhances customer experiences and boosts productivity. Utilizing tools like Microsoft Co-Pilot in email and Excel demonstrates this point; the significant value comes from how these tools are integrated into your processes to streamline operations and foster innovation. Just answering e-mail quicker is not going to get you all the way because everyone will have this access to these tools so it will be a hygiene factor. AI will be an addition to your hopefully already existing business development work and not a stand-alone effort. And here process and change are some of the keywords.

Picture 5: Automation is needed to scale

Process maturity as a key factor to value

The significance of being mature in process development, driving change, and building vision is vital. Maturity in these areas involves a clear understanding of your current processes, the quickness to implement necessary changes, and the insight to develop a long-term strategic vision. These elements are crucial for effectively scaling AI within your organization.

In summary

Successful AI adoption relies not just on technological prowess but also on strategic vision and change management to ensure these technologies are effectively leveraged to achieve business objectives. So now go do some AI and best of luck! And remember the Deerdata team is here to help and there are only good questions.