Start with problems, Sandbox, identify trust suppliers, a quick guide to start with AI

With 77% Of the companies that already use or explore the use of AI, and more than 80% say it is a priority, leaders are eager to obtain the maximum value of technology. However, the volume of available solutions and the onslaught of marketing messages that accompany them can hinder the search for a clear path. Here are some guidelines to help you evaluate the abilities of AI tools and determine the best option for your organization.

When the media praise a particular platform, or discover that their competitors are using it, it is natural to ask if you should do it too. But before examining a new system, identify the problems facing your business. What are your key challenges? Your central needs? Once you have redirected your approach, replicate the solution you are considering through this lens.

If AI technology solves well -defined and measurable problems that your company has been finding (that is, automating routine tasks or increasing equipment productivity), it is worth exploring the tool. If you do not connect directly to solve your problems, continue. AI can be incredibly powerful, but has limitations. Its objective must be to apply only to the areas where the most significant impact can have.

Pilot programs and experimental budgets

When it has determined that a given system can strategically support your needs, you have met the first necessary criteria, but this does not mean that you are ready to make a purchase. The next step is to take the time to test technology significantly through a small -scale pilot program to determine its effectiveness.

The most valuable test uses a frame that connects to the performance indicators of the crucial key (KPI). According Google Cloud: “KPIs are essential in GEN AI implementations for several reasons: objectively evaluating performance, aligning with commercial objectives, allowing settings based on data, improving adaptability, facilitating clear communication of interested parties and demonstrating the ROI of the AI ​​project. They are critical to measure success and guide improvements in AI initiatives. ”

In other words, your proof frame could be based on precision, coverage, risk or any kpi that is more important for you. You just need to have clear kpi. Once you do, it gathers five to 15 people to perform the tests. Two teams of seven people are ideal for this. As those experienced people begin to test these tools, you can collect enough entry to determine if it is worth climbing this system.

Leaders often ask what they should do if a supplier is not willing to make a pilot program with them. This is a valid question, but the answer is simple. If you are in this situation, you do not compromise more with the company. Any decent provider will consider creating a pilot program for you.

In addition, plan in advance and leave funds for an experimental budget of AI. Here it should be where it turns when you want to try several solutions without compromising resources. Even if everything seems to go perfectly, give your team a lot of time to familiarize yourself with technology and adapt before making a purchase or expand.

Prioritize data security and provider transparency

When you consider a platform, remember that it is not only evaluating technology but the company behind it. Suppliers must be crossed both scrutiny, if not more, than technology itself. Be sure to work only with suppliers that maintain the highest standards in terms of data safety. They must adhere to the global standards for data protection and ethical principles of AI, and the platforms themselves must be certified as soc 2 type 1, SOC 2 type 2, the General Regulation of Data Protection (GDPR) and ISO 27001.

In addition, verify that your suppliers are not using your company’s data for training purposes without explicit consent. Zoom virtual meetings provider is an example of a popular company that had planned To harvest customer content for use in their AI and ML models. Although they finally did not carry out these plans, the incident should generate concerns for companies and consumers equally.

If a dedicated leader in charge of this area places, this person can administer all data security needs and guarantee compliance with the organization. This may seem unnecessary and additional work, but it is essential. Remember that all that is needed is a unique data violation by one of its suppliers to lose the client’s confidence, if not its customers.

Final thoughts

Leaders must use a structured approach to evaluate AI solutions to obtain maximum value of them. Grant first in problem solving, closely followed by tests and pilot programs, data safety and tangible value identification. AI can be immensely powerful, but only when applied to correct problems after careful selection and implementation.

Arjun Pillai is co -founder and CEO of Docks.