Start with problems, identify sandboxes, trustworth vendors – a quick guide to getting started with AI

and 77% Leaders want to get the greatest value from technology, as more than 80% of companies already using or investigating AI use claim to be their top priority. However, the onslaught of available solutions and the marketing messages that accompany them can make it difficult to find a clear path. Here are some guidelines that can help you evaluate the capabilities of your AI tools and determine the best fit for your organization.

When media praises a particular platform or discovers that a competitor is using the same platform, it’s natural to wonder if you should too. But before examining the new system, identify the issues your business is facing. What is the important issue? That core needs? Once the focus is redirected, reconstruct the solution you are considering through this lens.

If AI technology solves well-defined measurable problems, then if the company is encountering (i.e. automating daily tasks and increasing team productivity), then this tool will explore It’s worth it. If you do not connect directly to the problem resolution, proceed. AI is very powerful, but has limitations. Your goal is to apply it only to areas where it can have the most meaningful impact.

Pilot Program and Experimental Budget

When you determine that a particular system may strategically support your needs, you met the initial required criteria, but this does not mean you are ready to buy. The next step is to spend time testing the technology extensively to determine its effectiveness through a small pilot program.

The most valuable tests use a framework that connects to key key performance indicators (KPIs). According to Google Cloud“KPIs are essential for the deployment of Gen AI for many reasons. They objectively assess performance, adjust business goals, enable data-driven adjustments, improve adaptability, and clear stakes Developers’ communication and demonstrates the ROI of AI projects. They are important to guide the success and improvement of AI initiatives.”

In other words, your testing framework may be based on accuracy, coverage, risk, or KPIs that are most important to you. You need clear KPIs. Once that’s the case, gather 5-15 people and run the test. Two teams of seven are perfect for this. Experienced individuals will begin testing these tools, allowing them to collect enough input to determine whether this system is worth scaling.

Leaders often ask what to do if the vendor is not planning on doing a pilot program with them. This is a valid question, but the answer is simple. If you are in this situation, do not involve further company. Any valuable vendor will be honored to create a pilot program for you.

Additionally, plan ahead and secure funding for an experimental AI budget. This should be a place to go when you want to try different solutions without over-relining your resources. Even if everything seems to go seamlessly, give your team plenty of time and adapt before you get used to it and make purchases or scale up.

Prioritize data security and vendor transparency

When considering a platform, don’t forget that you are evaluating not only the technology, but the company behind it. Vendors need to do as much scrutiny as the technology itself. Be sure to work only with vendors that maintain the highest standards from a data security perspective. It must adhere to global standards for data protection and ethical AI principles, and the platform itself must be certified as Soc 2 Type 1, Soc 2 Type 2, General Data Protection Regulation (GDPR) and ISO 27001.

Additionally, make sure that the vendor is not using company data for AI training purposes without express consent. Virtual Conferencing Provider Zoom is an example of a popular company. plan Harvest customer content for use in AI and ML models. They ultimately did not implement these plans, but the incident should raise concerns for both businesses and consumers.

Posting dedicated AI leads for this subject will help this person manage all their data security needs and ensure compliance with the organization. This may feel like unnecessary, additional work, but it is essential. Remember, what you need is a single data breach by one of your providers to lose customer trust.

Final thoughts

Leaders should use a structured approach to evaluate AI solutions to get the maximum value. The focus will be on problem solving first, followed by testing and pilot programs, data security, and specific value identification. AI can be extremely powerful, but only if applied to the right problems after careful selection and implementation.

Arjun Pillai is co-founder and CEO Docketai.