AI, and specifically Generative AI, has been heralded as the key to digital business transformation and future competitiveness. But infusing an organization with insights and automation requires more than just a technology.
Digital and AI transformations are common, but moving from pilots to large-scale implementation requires fundamental changes to talent, operating model, and technology and data capabilities. This post will examine some best practices we’ve learned in helping our customers use AI for digital transformation.
If you think about AI as a marathon, a key predictor of success is what you prioritize at the starting line. Always begin with a business problem you are trying to solve. When business leaders identify what they would like to improve, developing a technology roadmap to eliminate that hurdle is easier. Don’t invent problems to solve with Generative AI, but instead focus on addressing existing pain points in the company.
While we’re on the subject of technology, don’t assume that Generative AI is the lever you simply pull to solve all problems. While it gets most of the press right now, it’s not always what your company needs. For example, if you are trying to optimize fulfillment and replenishment by predicting which new customer orders will become steady new business, you need traditional AI models, not GenAI.
Another roadblock to AI is talent acquisition. Talent is essential to long-term success in digital transformations, and traditional companies that are serious about their transformations manage to get the right talent by committing to a modern technology environment. The market for AI resources is extremely competitive and the candidates who consider working for you want to know that their skills won’t whither and perish once they’re hired. You can secure the best talent by modernizing your technology stack, software engineering methodologies, and the way you manage data.
When it comes to the effect of organizational attitudes on successful AI and digital transformation, all companies need to embrace the mindset of being a technology company, no matter what industry they are in.
Even if technology is not the core business, technology has never been more important in creating differentiation, and there is no option other than excelling at AI and software development.
You start small in one or a few departments and gain expertise. Once everyone understands the value of AI, the expertise is shared among other business areas and they soon develop their own capabilities. This does not mean that your IT department is out of the loop – they will still be your foundation around data, tools, and security.
Digital and AI transformations have become crucial for businesses in today's rapidly evolving landscape, and organizations should take an approach that focuses on solving real business problems and meeting customer expectations, prioritizing talent acquisition, and taking a gradual learning approach.
Business partners with expertise in AI applications, such as our practice at LRS, can help you implement AI and create a strategic AI roadmap for your business. If you are interested in learning more about how LRS can help you change your business with traditional and Generative AI, please contact us to request a meeting.
About the Author
Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.