Introduction

Zoho and how we see the future of sales with AI. And I'm not sure how many of you know Zoho already, but I will give a quick introduction about Zoho, what we do, kind of the capabilities that we see in the field of AI, how we implement them, and also what we see of where the future with AI is going to and what you will need to do to be able to cope with that, basically.

Overview of Zoho

So we are a SaaS company and we build AI based or AI powered software for enterprises and we are mostly known in the Asian and American sphere but now also get a foothold in Europe. We have over 100 million users worldwide and We have built up an infrastructure of SaaS applications for business.

We started from scratch with like a CRM system to manage your contacts and sales processes. And due to our privacy approach where we want to have sure or where we want to make sure the data that customers share with us is not shared with external vendors or external parties. We started to build our own other applications like you need to run your own servers, you need to have own marketing software, you need to have own bookkeeping software and all of that.

And as most vendors nowadays require that they get access to your customers' data and also sell them to other companies, we have built this approach where we build all these applications ourselves. And we have come to a stage now where you can basically run your entire organization on Zoho and the application universe of Zoho. And this goes across sales, marketing, HR, business intelligence, like the whole portfolio that you might need in a business.

And we have about 15,000 employees. We run in 150 countries all over the world. And we have built a full ecosystem of integrated applications over the last 25 years.

The Role of AI in Business

292% of CIOs believe that in the next year their companies will have AI applications integrated in their business models and they also get pressure from the CEOs to make those AI applications productive and to bring return of investment. For this, we see one big issue with the current infrastructure of how the world operates with AI.

And here's an example. You have a customer service center, for example. This customer service center operates with AI.

When we build our applications, our approach to AI is that we think that AI should be designed in such a way that basically you don't really notice that you use AI and that the AI is doing all the heavy lifting for you while you just do the things that you want to do and need to do. And for this, we have built over the last years, like the first time we started was 2012, where we've built our own AI system that is called Zia.

And we have integrated Zia in almost all our applications with certain functionalities, particular features, everything that you need to have like a productive work environment. This can go from like typical CRM functionalities like building workflows automating processes having data prediction like you can see what data is about to come and like all of these

functionalities are standalone functionalities in these applications but what you really want to have in a company that is running efficiently and is future proof for AI is to have all these things interconnected and I appreciate also the presentation before because I think it's a good point there they also make across those different applications we just bring all these applications in our system together but we're also integrating with third parties so this would be for example an extension to like bring all these applications together, because in the end the systems need this data on the back end.

Zoho's AI Applications

Here are a few examples of what we can do with our system. For example, we have a voice software, for example, where you can have a conversation with your customers, sales conversations, and these sales conversations get converted into text, and these texts can get automatically summarized, and you can get data out of them really quickly.

We have recommendations like you maybe know this from Amazon where you purchase certain things and you get recommendations what other people have purchased. You can supply your sales agents with those information on the go so they know what can be provided to the customer.

We have a sales chat agent where you can, like this is our AI, where you can chat with the AI and request data about the customer that you might need or about a certain case. Again, all these applications are standalone things in the CRM, for example. But what you really need is the context of all the applications.

As mentioned in the presentation before, you need to connect those data tables across applications to make a common sense out of what's meant, what you need, and how to bring some things together to bring a new output out of this. So what we have for this, for example, we have a system in the CRM where you can ask the system to write an email and have the data that comes across from all the organization together to feed the context of the elements you want to create.

Also, what we have is Zeo Search. It is a feature that you can use to search certain things across all the applications you have in your business. For example, some customer calls you and wants to have an invoice, and then you can just use the search bar, search for this customer, and it searches in your email inbox, in your invoicing software, in your file structure, and wherever it could be, it will try to find out where the information is that you search.

What we also have is a chat system for this, which also operates across the applications. And here you can get direct insights in what's happening in the backend. You can get data and BI information about what's going on in my company, what happened last month, what's going to happen next month, all those kind of things. And you can get really detailed cross-application insights here.

Challenges and Innovations

But again, What I mentioned earlier, the CIOs are facing surging expectations from CIOs to bring return of invest and to make an impact.

And for this, we have, for example, an application that's called Zoho Creator, where you can build your own applications via drag and drop. And it is integrated with ChatGPT. We have like kind of a zero knowledge integration with ChatGPT, where you basically give you requirement you need for your application. Then ChatGPT gives you an architecture of how this application should look like, feeds it back to our own AI, and our own AI is building the application on top of that.

For this, I will just quickly share you a demo. And for this, I'm just building right here, maybe in one minute or two, an application with our AI Zia. And I just put the microphone to the side for a second. And if you have an idea what you want to build, you can let me know.

Aside of this, I will just go ahead and create an application for an Let's say I want to have an event and I want to have a ticket system where I can track the tickets. And if someone has paid their invoices, so I can let them in or not. And also I want to have meetings scheduled with them for after the event.

And I just write a prompt, one second. Um. So I've written now for everyone that cannot read it behind, please create me an app where I can manage tickets for an event and can identify who has paid their invoices so I can let them in. Also, I want to manage appointments in a calendar for after the event.

So now I press just create use case for this creator app. It then fetches the requirement with ChatGPT. It says, oh, maybe you need this, you need these features, you need these functionalities. And then I just click on Create Application.

It now assembles what does ChatGPT mean with these designs, what UI elements you want to have, how should they function, how should they interact, how should the data in the back end look like. You get it fed with some demo data. automatically. And in the back end, you can see how the data tables are connected, how they're intact with one another.

So you can feed those things into the application. And then I can just click on Create. And we'll generate a runnable application that I can use for this purpose. It will feed it with the demo data, takes a few seconds.

And on the spot, I have an application that I can use with my sales team, for example, at an event and say, hey, I want to collect my leads. These people have paid my invoices. I want to have, for example, here I can see who has paid which invoices. Here's the event.

I can add new events. And maybe I also have a calendar here where I can schedule my calendar with those things. So this is what we understand an agile AI usage where you use on the spot the AI for new use cases and integrate this with your holistic application ecosystem that you have.

So you can not only run all the use cases you want to have for your AI system, but you can also create new use cases and you can create new workflows, new processes and and adjust to new requirements in the market really fast.

Conclusion

In summary, I can say for future of AI, you will require context, so all the applications should be connected somehow in a deep level where you can bring all these data tables together. We work interconnected systems, the context, like what is meant by this invoice, what is meant by this project, what is meant by those numbers that I see here in front of me.

And you will require to be agile in order to be able to compete with all the companies that are on the same race at the moment. And this is our perspective from Zoho.

So start prompting, start digitizing. And I wish you all a nice evening here. And we also have some goodies over there if some of you are interested. And that's from my side. Thank you.