Meet Emma, CEO at Avaus, a leading consultancy in customer data and AI. Emma's unique talent blends sharp thinking, strong determination, and boundless energy. With a solid strategic approach, Emma is known for sharing pragmatic advice for business success in the domains of data-driven sales and marketing. Don't miss her insights at the upcoming AI: Beyond the Hype
If we want AI to yield a sustainable impact on our businesses, we need to implement it on a wide scale within the organization. However, this is not an easy feat. While many organizations are testing and implementing AI solutions, the pace is disappointingly slow. It's a common pain point to play around with AI initiatives, trying new tools etc, but failing to reach a positive ROI on investments in data, AI and automation.
Starting AI implementation in the domain of sales, marketing, and customer service is appropriate, given the potential for high-value realization and relatively low risks.
But merely integrating AI into one or two applications won't cut it. To truly capture the business potential of AI that is present already today, it needs to be infused into multiple processes, creating economies of scale that yield significant leverage.
Success in AI implementation requires robust leadership and a blend of technical and strategic skills to bring about the necessary changes in work methodologies.
In areas like marketing, sales, or service processes, you need data, technical capabilities, and a commercial strategy that positions AI as a driving force. It's a complex mix requiring diverse skills, and the challenge is worsened by organizational silos.
At Avaus, with over a decade of experience, we have navigated the AI landscape, helping numerous organizations, including a major Swedish retailer, a large industrial company, and a global tire manufacturer, in rolling out diverse AI solutions.
Having witnessed common mistakes in AI journeys, I've noted that many organizations underestimate the complexity of scaling up, assuming they can handle it internally after initial experimentation.
Most would however benefit from a framework – a systematic methodology for AI implementation.
The business results that AI can deliver are substantial, so investing in scalability early on is worthwhile. Delaying or changing methods after years of experimentation puts organizations at risk of falling behind more forward-thinking competitors.
Don't miss experiencing Emma live at the Münchenbryggeriet on February 13th, or take part in our live broadcast. Whatever you prefer, book your ticket now!