Is your team struggling to effectively integrate AI? Many organizations find it challenging to identify the right use cases. This article explores using education, workshops, data readiness, and IT collaboration to successfully integrate AI.
By: Carl-Johan Färnström, Expert, on November 15, 2024 | Reading time: 5 minutes
At Curamando, we have now done multiple AI projects for our customers and have learned some valuable things regarding how to implement AI in existing business processes successfully.
What we see is that a lot of companies put a lot of effort into upskilling IT departments on AI technology. However, they fail to integrate AI into the business because the business does not understand how AI can work to transform key processes. The technology is there, but the use cases are not.
Various types of “Strategic AI task forces” can mitigate this, but the true magic happens once all business users and process experts understand the technology better. Then, innovation sparks from the bottom up, and business users will find use cases everywhere they look.
Here are some key enablers we’ve gathered to help you put AI on the agenda for every team:
Education first
Not surprisingly, AI training is the number one enabler. Our initial initiatives with prompt schooling for customers were fruitful and helped teams and individuals understand the basics of generative AI. However, in our implementations, we’ve found that having subject matter experts show team members practical examples of how to work with tools like Chat-GPT, NotebookLM, and Midjourney in a slightly more advanced way —such as uploading files, creating tables, building libraries and notebooks, and continuously fine-tuning—was the real key. The examples didn’t have to map exactly to the team’s tasks and responsibilities. As long as they were within the same area, they helped open the team’s eyes and minds, not only regarding generative AI but AI as a whole.
Workshops to unleash creativity
After initial training, workshops become a creative power studio. By getting teams together to take a hard look at business processes, we could pinpoint where AI could make a real difference. These sessions often led to lightbulb moments on how AI could tackle specific issues. More importantly, they helped teams see just how much of their work can be streamlined, making everything run smoother.
Put data on the agenda
Data is the backbone of any AI project. A well-structured data foundation and robust data management processes are essential for making AI initiatives work. However, we have seen that when teams innovate around AI in their business processes, data management comes into focus, and people understand that a key to getting their idea to work is to have a good data structure. So, the AI projects are actually fostering a data-driven culture.
Ensure IT compliance
An absolute key of the AI initiatives we have done within our client’s IT environments has been to find a way to securely use AI models to process data – within those environments. Most IT environments have these capabilities, and it’s mostly a matter of finding a suitable architectural setup. But once this hurdle is clear, you allow teams to think creatively about AI solutions and create good innovation.
Strategic alignment
Some AI initiatives that came up during our client projects required long-term planning and strategic alignment. Also, the number of initiatives that can start coming from process experts will require priority and alignment.
But how do you align an AI project with a five-year plan when the use case it addresses might not even be valid in five years? AI technology is simply evolving too fast. We identified three success factors for this:
- Scope use cases using the double diamond model outlined by Lisa Gudmundson in this blog post
- Break down larger use cases into manageable components and address each iteratively. Focus on designing, prototyping, and scaling each component to gradually build towards the comprehensive solution.
- Positioning people who understand both business and AI technology close to management and strategy. Offering advice on direction rather than a plan, aligning the existing strategy with the opportunities that can come from AI.”
Conclusion: From Vision to Reality
Creating innovation and making AI a competitive edge for your business is not an IT project. It requires a people-centric approach that sparks creativity and fosters a growth mindset. When change initiatives come from the ground up – process optimization, data readiness, and IT collaboration come easy and enable businesses to take a leadership position.
Curamando is founded on a belief in duality, combining management consultancy with engineering. We help clients with their digital transformation, from strategy to execution.
Read more about our AI offerings.
