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Since its launch in November 2022, ChatGPT and other AI models have taken the world by storm. It’s no wonder: the rise in effectiveness using such tools is second to none. If there’s anything that’s easy to use and makes one more productive from day one, you can be sure the adoption levels will skyrocket.
While some perceive AI as an inflating bubble, others are joining the race to introduce the best AI-powered products out there. Which side will you take?
The AI race has started, whether you’re ready or not. Since ChatGPT’s record adoption rate, software giants like Microsoft, Google, Salesforce, and HubSpot quickly decided to enhance their products with AI. Whether it’s Microsoft’s Copilot, Google’s Gemini, Salesforce’s Einstein, or HubSpot’s ChatSpot, these tools are changing how we work and making us more productive. According to MIT, Generative AI can improve worker performance by as much as 40% compared to workers who don’t use it.
If your product users haven’t asked you about your planned AI features yet, they will soon start doing so. As Torabi puts it, AI is no longer a choice but a strategic imperative for product management. This, among all the other features product managers have in their backlog, creates additional pressure and FOMO (fear of missing out).
“AI is no longer a choice but a strategic imperative for product management.” Nima Torabi, Advisor at Loyal VC
As tempting and urgent as launching your next AI feature may seem, it's vital to think twice about what your customers can achieve with such a capability.
In some cases, AI offers an obvious extension of the core product's capabilities and, if you closely observe customers' use cases, sets your next release up for success. A typical and unsurprising example is customer support applications using chatbots to deliver relevant answers to customer queries. AI has an indisputable place in such cases, and we can all clearly picture the smart and efficient use of AI in similar applications.
What if your product is more complex, offering multiple layers of functionality and helping your customers achieve a plethora of different things? How do you incorporate AI into your product so that it fits seamlessly with how customers use your product?
Instead of developing a single-purpose AI feature that may result in very low adoption (and thus a waste of your precious development resources), you can open your product to virtually unlimited AI-powered usage. This is where no-code automation comes into play.
Let's set the common ground first. Even today, a tremendous amount of manual and mundane work is performed by highly qualified workers. Not everyone can code, take advantage of API possibilities across multiple platforms, and automate their routine work. Nonetheless, a movement is changing this paradigm: no-code automation.
It started with integration platforms as a service (iPaaS) products like Zapier or Make, which allow you to connect various well-known products and send data between them. Power user of the Internet can now automate their work by connecting various products—all without knowing how to code. (That’s where the term “no-code” comes from.)
No-code automation refers to the use of software products to automate workflows, integrate different applications, and sync data between them without writing code. AI-powered no-code automation does all that, empowered by AI functionalities.
The beauty of no-code automation is that it typically comes with an intuitive, visual interface for people to navigate easily. Now, what's in it for you as a product manager, you may ask?
No-code automation is becoming an embeddable component similar to payment methods (think Stripe), analytics tools (think GoodData), or other white-label platforms that shorten the time to market and enrich your product with valuable features.
In other words, you can now upgrade your SaaS product with no-code automation without developing it from scratch. This creates a perfect environment that 'just' needs to be enhanced with AI to do the real magic.
Imagine your customers choosing a trigger for the automation (like a new file on Google Drive) and chaining different actions following it (like summarizing the document via AI and sending a notification on Slack). The combination of an intuitive UI, pre-built integrations to hundreds of applications, and AI models gives your product users all they need to use AI from within your product and in the context of their choice. One product, one UI, but tens of different uses of AI.
Sounds too vague? Let's look at a few examples of AI and no-code automation in action.
One can probably think of dozens of different use cases for AI-powered no-code automation. We'll cover five that we see our customers implement and succeed with.
Imagine you build a CRM and offer the obvious features such as contact and deal management, email marketing tool, and other functionalities your customers would expect from a CRM. To help your users become more productive, you now adopt a (white-labeled) no-code automation designer powered with AI, helping sales reps build a sequence of emails and social media interactions with content automatically created based on the (unique) history of each contact.
In other words, you'd help your customers automate a hyper-personalized sales conversation from A to Z, using both AI and no-code automation.
Here's how such an interface would look if you chose Appmixer to deploy AI-powered no-code automation.
The beauty of the no-code and AI marriage? If a different customer of the same CRM application wishes to achieve a different kind of (AI-powered) automation, she has all the tools to achieve that—build a different workflow and use artificial intelligence in a different context, for example, calculating the probability of a deal being closed based on historical data.
Let's pause here for a second. The new concept of an AI-powered embeddable no-code automation offers maximum flexibility to SaaS end users. Using an intuitive UI, the user can choose a trigger that starts the automation and chain an unlimited number of actions that follow. Both triggers and actions represent API endpoints of almost any application (think Salesforce, HubSpot, Asana, you name it). These endpoints can also be within your own SaaS product, meaning that the automation can run solely based on the capabilities of your own API. AI then sits among any of the actions and adds advanced logic to the workflows.
So far so good? Let's look at another interesting use case.
CMS platforms and website builders, such as Webflow, offer easy ways to create, publish, and manage content. However, when a new content piece (like a blog post) is created and published, wouldn't it be nice to share it automatically on social media with good copy that follows the company tone of voice and uses the customer language?
Not surprisingly, no-code automation and AI offer a very sophisticated way to achieve that. As the workflow below shows, with every blog post published on a Webflow-like platform, a LinkedIn post is created using AI and then sent to Notion to be approved and published by the social media team.
Simple yet very effective automation that involves human decision-making, but lets AI do the hard work.
The main point? We looked at one use case in the context of a CMS application, but again, if the need arises for a different usage of AI in the context of the same CMS application, the no-code automation designer satisfies it just as elegantly.
Cybersecurity has become a major concern with the rising number of cyberattacks. Security automation typically helps companies react to threats and attacks and take actions based on internal policies and processes.
The use of no-code automation and AI can be represented as the image below shows: Every time a security alert is received, an action is suggested based on AI input (taking into account the company policies and best practices), and a ticket is created in Jira for a security specialist to evaluate the proposed solution and potentially implement it. If the alert is tagged as high priority, the security team is also notified through Slack to react immediately.
If building a customer support application, AI can digest the documentation of your customers and help them respond to support tickets. Whenever a new ticket arrives, AI can read it and create a response suggestion. The support agent can then review AI’s response, adjust it if necessary, or simply hit the approve and send button.
Data enrichment is another area where AI can be highly beneficial. For instance, when creating a new contact or company in a CRM (or other) system, AI can augment the data using web-available information and update the record back into the system. This ensures that teams have comprehensive context on their partners, customers, or potential hires. As the workflow below demonstrates, using embedded iPaaS solutions such as Appmixer makes automating such tasks simpler than we might even want to admit.
SaaS product managers can think of AI-powered no-code automation in multiple ways. Let's go through the three obvious benefits and uses of AI-powered no-code automation:
As Appmixer customers experience, embeddable no-code automation powered by AI enriches their SaaS in just days, using only a fraction of the development resources. This presents a great opportunity in a world where AI is just starting. No one can foresee the future, and while launching AI features may seem logical and urgent, adoption is what every SaaS company should prioritize. Having a way to quickly test and evaluate an idea can save hundreds of thousands to millions of dollars.
The AI race does not require every player to build everything from scratch. On the contrary, if companies can leverage existing solutions, their time to market can be significantly faster—even for such advanced capabilities.
Ultimately, it's about the value you bring to your customers. Instead of building a single-purpose AI feature that may or may not meet their expectations, you now have the ability to offer context-based artificial intelligence that naturally augments your product. However a customer wants to use AI in your platform, she has everything needed to make it work.
If AI sits in your backlog, you now have a way to deploy it quickly and with very little R&D effort. Companies choosing Appmixer can launch the above-mentioned no-code automation features, including AI, in just 30 days.
Don't build rigid AI functionality that will see low adoption and distract your development team from what's important: building features that your customers value, use repeatedly, and ultimately pay for. Give your SaaS customers the option to use AI in the context of their choice, empowered by no-code automation capabilities that make your product even more flexible. You can do it now. And your journey starts here.
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