The current generation of generative AI is intuitive, powerful, and talked about as soon to be pervasive. It has also been hailed as the ultimate waste of time, a technology whose development shows no signs of catching up with the hype cycle and whose capabilities have fallen short of what was promised.
To get the most accurate picture of the current state of AI, companies need to listen beyond the current conversations among technology influencers and hear what other customers are saying. And in this case, they are expressing skepticism about AI for AI's sake. But if AI can help improve workflow and decision-making, they will use it. In some cases, you might not even call it AI, even though it already is. It only helps them do their job better. Many vendor technologies weave AI into the fabric of their SaaS tapestry, running in the background and performing tasks behind the scenes, whether it's complex predictive analytics or simple task automation.
Consider that AI has developed on a rapid timeline. Initially, rudimentary AI could only do a fraction of what we know today. The features can be thought of as ingredients for a recipe, and given a finite set of ingredients, there is a limit to the number of recipes a user can come up with. Perhaps it was a simple and situational recipe back then. However, if the number of ingredients increases by even one, the number of possible recipes increases exponentially. Consider adding one more digit to the dial lock to enable even more sequences.
After all, companies cannot succeed with AI unless they can directly apply AI discoveries and capabilities to business intelligence (BI). This is what businesses need now, and expectations of future AI capabilities will do little to solve the problems they face today. Instead, successful companies try a few ingredients at a time before jumping right into complex recipes, and practice a few appetizers to satisfy hunger in the short term before moving on to the main course. To do.
Here we detail how some companies maximize potential with minimal materials.
Beyond industry standards
For Servifácil, one of Latin America's top gasoline retailers, the promise of AI is to handle many of the repetitive, daily tasks of its employees, freeing them to focus on what matters most. It was about future-proofing the business. The company is also blind to how well its operations are doing, especially its sales processes, and how quickly and smoothly it is acquiring new customers, and AI needs the data it needs to guide organizational transformation. I was hoping that they would provide it.
In searching for the right solution, the company needed to consider whether a particular vendor's AI potential was worth sacrificing its current usefulness to meet its current business needs. We also wanted to ensure that the software was easy to learn for everyone in the organization, as low adoption rates would make the solution less valuable. Still, other companies in the industry were stuck with spreadsheets and were past the point to at least upgrade to something centrally managed. Ultimately, he decided to go with Zoho's CRM, analytics and desk software solutions and an integrated system that incorporated his AI capabilities, giving his employees a little more visibility across the board. I expected to benefit from it.
Servifácil was hopeful that AI would produce results, but it didn't expect its new software to be as successful as it was. Since implementation, the company has doubled the amount of gas it sells to customers month-on-month and almost tripled its total contracted volume. Much of this is due to data generated by integrated systems, which can be automatically synthesized by AI and used to instantly inform process changes. Rather than waiting for AI to revolutionize the way we do business, Servifácil is leveraging the technology to meet current business needs and exceed them in the process. AI played a supporting role, but the company was smart enough to make it an advantage first.
continue the mission
Recently, Luxer One, a maker of smart locker systems for residential and commercial properties, recognized that AI would eventually play a central role in their business. But there was no rush. The technology was fairly new and the hype was out of control. Rather than quickly switch processes and cede full control to AI, the company started small to allow AI to handle specific questions.
First, Luxer One integrated SalesIQ and ChatGPT into its support operations and used Zoho Analytics to determine the success of this change. Things went well. Not only has Luxer One used that information to inform the development of new products, but it has also been able to present data points to prospective customers and demonstrate, with little ambiguity, how impactful its services are. It's done.
The effort was successful, but Luxer One was still valued. Rather than rushing to expand its use of AI, the company dug deep into the results already generated, stored, and monitored from Zoho CRM. Employees combed through chat recordings, calculations, and special scenarios to ensure the AI was not behaving suspiciously. This human failsafe helped the company understand how his AI would work and provided an opportunity to course-correct before deploying the technology to a larger organization.
Currently, Luxer One is opening up the use of AI to developers, but with one caveat. It can only be used for specific tasks or routines that are deployed one at a time. Within these guardrails, the company can ensure that AI is applied strategically rather than comprehensively, eliminating errors and positioning itself to be leveraged as technology evolves. . This approach also allows Luxer One to evaluate the AI against the current process before trying to bite off more than it can chew.
single source of truth
One day, AI will be able to handle a significant portion of a company's tasks without much oversight. However, there is a long way to go to get to that point. Currently, the technology is error-prone and unreliable, especially when companies learn that AI is often running in the background, collecting data for learning purposes.
There is no doubt that this technology will have an impact on the industry, so companies need to start testing AI, but in order to do so in a measured, step-by-step approach Demonstrated by Servifácil, luxar one, and many other mid-sized companies. A single source of truth, ideally a centralized CRM, makes the process more effective and acts as a human bumper to keep the AI from going off track. To create a new recipe, you need to make sure each ingredient is ready to be added to the mix.
We look forward to continuing this conversation with our customers in June. I'm looking forward to meeting many people. Zoholic in Austin.
