An AI Solution Architect is essentially your point person in between a few crucial steps, down the road to AI adoption within your business.
The first step for the AISA is understanding the business goals and turning those in to SMART objectives. Then mapping out a deployment plan to see if those objectives can be turned in to strategies that can actually land e.g is the tech stack a match, is there a legal implication to the automations, what could go wrong?
Setting KPIs is the next and crucial step because measurement is key to gauging success. Are you playing for an efficiency game, a cost-saving, a customer experience improvement or an employee experience? Having the right KPI and metrics in place will tell you how you are doing.
Finally, priority setting. Sitting with business function leaders and articulating the roadmap (which will eventually inform the workflows) means not only is the critical path correct, but resource allocation is clear from the outset and any gaps can be plugged.
Delivering project value to senior leadership is not always about what you did successfully, it's also about reducing risk via thoughtful planning.
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