There’s ALOT of talk about AI.
Many digital agencies claim to have it, few actually do.
Most owners we speak to don’t even care to understand it they just want
to know how it will impact their business.
If you’re a decision maker, below are a few tips to explain the steps businesses can take to integrate AI in your organization and to ensure your implementation is a success.
1. Think about what problem you’re trying to resolve first. Is it chat? Using your data to build personas for marketing? Supply chain management? Hiring? The list is endless when you look at all the arenas AI can be implemented. Create a problem priority wish list.
2. Next, assess the potential business and financial value of the various possible AI implementations you’ve identified in step one. It’s easy to get lost in “pie in the sky” and wanting to do it all. Practical AI applications can manifest in all sorts of ways depending on your organizational needs and the business intelligence (BI) insights derived from the data you collect. Enterprises can employ AI for everything from mining social data to driving engagement in customer relationship management (CRM) to optimizing logistics and efficiency when it comes to tracking and managing assets.
3. Acknowledge what your internal gap is. There’s a stark difference between what you want to accomplish with AI and what you have the organizational ability to actually achieve within a given time frame. Be realistic.
4. Once you’ve identified the steps above, bring in the chosen AI team you want to help navigate a pilot project. You don’t need a lot of time for a first project; usually for a pilot project, 2-3 months is a good time range. Begin applying AI to a small sample of your data rather than taking on too much too soon.
5. After the pilot project is completed, you should be able to decide what the longer-term, more elaborate project will be and whether the value proposition makes sense for your business. This will also give you time to see how the team cooperated and if you enjoyed working with the agency prior to committing to a long term AI implementation project.
6. Get Buy in from your team! Companies should be transparent on how the tech works to resolve issues in a workflow. This will give your company an ‘under the hood’ experience so that they can clearly visualize how AI augments their role rather than eliminating it. This comes up alot and many team members may be wary of technology that can affect their job, so introducing the solution as a way to augment their daily tasks is important prior to launching a big initiative.
7. Build with balance! Too often, AI systems are designed around specific aspects of how the team envisions achieving its research goals, without understanding the requirements and limitations of the hardware and software that would support the research. Build flexibility into the budget when making the investment so you’re not caught off guard.
Ready to GO AI?
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