I’m thinking about experimenting with AI, and I don’t want to go it alone. Where do I start?
AI is in the news seemingly every day now. Maybe you’ve been thinking about how to get started using AI to help your workers (and yourself!) on the job. Perhaps you talked to several colleagues, friends, acquaintances in the business and have heard a few horror stories. (My favorite: “We’ve been trying to implement an AI bot to assist our customer service agents — for three years! — and it still doesn’t work.”) It’s just going to take too long to go it alone.
So you’ve decided to get help. Where do you start? How do you assess your needs?
Step 1: Set clear goals. What do you want to accomplish? Do you want to develop predictive maintenance? Do you want to improve quality control? Is safety enhancement important? How about regulatory compliance automation or personalized customer service? What’s most important to your organization?
Step 2: Determine pilot scope. It’s always easier to start small, of course. Starting small also makes it easier to get the requisite approvals. Do you want to focus on a particular department or process, just to start? You could start with Manufacturing and Production — perhaps Quality Control or Inspection. You could start with Supply Chain and Inventory Management — Demand Forecasting or Logistics Optimization might be a good process to start with. Customer Service and Experience is a popular place to start because it’s relatively easy to implement a Chatbot or Personalized Marketing through AI. In the areas of Sales and Dealership Operations, you might choose lead scoring and management or price optimization. Of course, these are just a few ideas for experimentation.
Step 3: Gather stakeholder input: Now that you have an overall idea of goals and scope, it’s essential to talk to as many stakeholders as you can. I’ve seen this be the key to success (or lack thereof) many, many times. But how do you gather stakeholder input at scale? Here are just a few ideas: Conduct surveys, interviews, or focus group discussions to collect qualitative and quantitative data on how things are currently done. You can ask about processes, challenges, the reasons behind doing things a certain way… many times you will uncover people doing things as a “workaround” when they aren’t even aware that the current process IS a workaround.
Step 4: Document current processes: When speaking with many different workers about many different procedures, it’s easy to forget details that become important later. That’s why it’s so important to document how things are being done today. Through mapping out processes, you can make note of existing workflows and processes. While you are making notes, try to identify repetitive, time-consuming, or error-prone tasks. These are prime targets for AI help. It will also be very important to make note of what data resides where. Is data currently being collected? How is it being used? What is the quality of that data? Is it easy to get to?
Step 5: Evaluate technological readiness: What is the organization’s infrastructure like? Can it support AI initiatives like what you are proposing? If you are planning to host your AI on-premises, do you know what’s required regarding computational power, storage capabilities, and network infrastructure? Consider knowledge and expertise as well. Are there any skill gaps present? Occasionally I’ve come across internal teams that have dabbled in AI that also have benefited from a partner like Humaxa. Otherwise, the AI implementation might have gotten bogged down or taken years to implement. It’s also possible that members of your team would benefit from additional training or mentoring from others who have successfully implemented similar technologies.
Step 6: Develop a roadmap. As with any experiment using sophisticated technology, planning is essential and can help everyone involved be held accountable. Prioritize possible projects based on your needs assessment. Determine which projects offer the highest value. You should also create a realistic timeline based on similar projects. The timeline should include implementation, key milestones, deadlines, and who is responsible for each. Risk management is also important. Try to identify any potential risks and for each, develop a mitigation strategy.
If you have thoughts or questions about any of these steps, let me know — whether you become or client or not. I’d love to help.
Carolyn Peer
CEO/Co-founder Humaxa
www.humaxa.com
carolyn.peer@humaxa.com
