AIOPS++
What is an AI strategy and how do you build one? We now live in an age of AI implementation. AI has completely revolutionised the way we work, interact and go about our lives. BY MICHAEL CHALMERS, MD EMEA AT CONTINO MODERN DATA SCIENCE is no longer about researching breakthrough AI, but focusing on solving business problems with existing tools and proven algorithms. From manufacturing to marketing, AI is increasing productivity and streamlining business operations. In an increasingly crowded marketplace, business leaders are looking to AI-driven solutions for an edge over their competition. However, many businesses adopting AI lack the key ingredients of strategy, operating model and execution framework necessary for achieving business-wide AI adoption. An AI strategy outlines how the technology will achieve set business objectives and, more importantly, identify AI assets that grant the business a competitive advantage and are difficult for competitors to replicate. Now that we know what an AI strategy is, here are some tips to create the right one for your business align your organisation and effectively execute.
1. Align your corporate strategy with your objectives During AI transformation projects, companies often make the mistake of separating the vision from the execution, resulting in disjointed and complicated AI programs that can take years to consolidate. This can be easily avoided by choosing AI solutions based on concrete business objectives that have been established at the project’s outset. It’s important to align your corporate strategy with measurable goals and objectives to guide your AI deployment. Once complete, the strategy can be easily escalated down into divisional- or even productlevel strategies. 2. Establish a multi-disciplinary AI team Form a multidisciplinary team to assess how the AI strategy can best serve their individual needs. Having members from different departments in your AI team, for example, web design, R&D and engineering, will
ensure your strategy will meet objectives for key internal stakeholders. You may not deploy the right strategy in the first instance, so iteration is crucial. By fostering a culture of experimentation you team will locate the right AI assets to form your unique competitive edge.
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