#AI@Work: Speed Isn’t Everything
The idea that quicker is always better isn’t true. Especially when organizations are going into new areas and training on new frontiers. Keeping the end in mind and proceeding thoughtfully might be a better approach to integrating AI than moving fast and failing. Many times, long term data will reveal what short term analysis just cannot. The fundamental risk of integrating AI and not having a plan is that of moving too far too fast.
Agile puts the emphasis on prototyping and getting fast feedback. The organization goes with the skills they currently have both cognitively and physically and they accept the constraints. This automatically limits understanding and monitoring. They look for short term gains and never look at long term impact. For example: AI recruiting software may save a few dollars in employees reviewing resumes. It may narrow down the pool of applicants quickly. But what happens to those people once the company hires them? Do they become valuable employees? Do they stay? Sometimes without thought and planning the gains from AI can be short-term and short-sighted. The new technology is not sustainable or supportive of the company’s long-term goals.
What can be even more frightening is that once the systems are in place, they stay there. The management team tells themselves that it is getting better. Eventually this will really work well. The future never materializes. No one is looking at the bigger picture. No one is stepping back far enough or long enough to realize the long-term effect of implementation on the organization. The technology is running the company rather than the company running the technology. Speed isn’t everything in managing big change. Putting new intelligent systems in place is not necessarily making progress.
Most change in operations comes about incrementally. Incrementally doesn’t mean it’s not worth trying or it’s not going to happen. Rather it means small steps that are monitored and reviewed carefully can and do bring about positive change. Agile is great once organizations have done the homework and as long as they continue to keep doing the work. It’s not a one and done thing. What Agile can help organizations avoid is getting so bogged down the entire project gets derailed or sidelined and nothing happens. Agile is best when it is combined with thought and planning about what those final deliverables are and how to measure success. Implementing AI responds best to working backwards or backward solution design. Defining the end result and then developing ways to know you are reaching it in both formative and summative ways keeps things on track and forces organizations to monitor the impact along the way.
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