It is not unusual to bring some of your own tools to work. Most chefs want to use their own knives, musicians use their own instruments, and so it would not be unreasonable to expect knowledge workers to have the same predisposition when it comes to software. Regardless, enterprise IT departments take a dim view of rogue software, or Shadow IT as it is also known.
To be fair to enterprise IT departments, software works best when it is integrated although integration is itself a spectrum. As a rule suites of software (Adobe, Microsoft) will all work together but often picking a team means organizations are sacrificing the very best options. For example, Excel is the king of spreadsheets but Google Docs is quickly becoming more popular than word.
Pick and choose
Instead of having to pick and choose, organizations can work around the limitations of software suites and invest in composable solutions which can be pulled together from the best in class tools. The large software vendors despise this solution because it underlines their ability to capture large sections of the market but the tide is already turning with initiatives such as open office and open analytics.
Integrated solutions allow for sharing documents, deriving statistics for business analysis and so on; it also means that files are transferable and interoperable. Overall, it reduces friction for the organization, even if there is a learning curve at the user level. Aside from convenience, the vast increases in ransomware attacks and corporate targeted scams mean running a tight ship is essential for businesses that operate at any kind of scale.
Shadow IT
With that in mind, shadow IT remains a thorn in the side of enterprise, with ChatGPT being the number one offender. Locking down laptops to try and stop unauthorized tool use is a mistake because it tends to encourage users to be crafty. But here’s a revolutionary idea, but why not give users what they want?
Interestingly, outside of the most technical roles it isn’t really the bones of apps that most users take exception to, it is the interface. Very few users wish their software was coded in Rust to prevent memory leaks, or is optimized to run on ARM vs x86 architecture. Instead, users want to be able to find the information they need and for the buttons to stay in roughly the same places between versions so at a critical moment they aren’t rifling through menus trying to find a function.
This user focus on interfaces means there’s an opportunity for developers to build products that are ‘universal’ (or that at least appear that way to users). This requires leveraging AI features to amplify the user experience with deeper analytics and customizations rather than watering it down.
Most developers are already adhering to software design philosophies like MACH, and any SaaS vendor that expects to be successful will adopt headless architecture in places so the solution can integrate with the kind of large suppliers that tend to buy capabilities from smaller developers for their own platforms.
The puzzle of AI
The last part of this puzzle is AI. This is a little more sophisticated than a ChatGPT plugin, and as a result it creates more value for customers. This isn’t to talk down rudimentary AI plugins, adding a ChatGPT interface for some data management and natural language processing capability is an effective way for businesses to dip their toe into the AI pool. That is why almost every business has their own version, but it doesn’t deliver on the potential of the technology of AI tools and leaves a lot on the table.
In terms of customer experience (CX) and user experience (UX), this is especially true because it limits AI to a small section of the interface. Instead by integrating AI throughout the interface it can become something much more effective, even revolutionary because with AI as a composing layer and AI products on the backend you can quickly iterate and deliver on new features because the solutions can interoperate more effectively.
AI is capable of something we’re loosely calling hyperpersonalization. Current efforts to personalize apps are limited to user profiles, a night and day mode for the interface, and maybe some limited language naturalization, but it’s all out of the box and fixed in the application. This customization isn’t just at the user level but the business level. Instead of buying the best CRM on the market, buy a CRM that feels like it was purpose built for your business, even if your industry has only existed for a few weeks. That’s how quickly AI accelerates the speed to market of products.
Even the basic features above are far from guaranteed. Night mode is a hugely popular feature because it mediates the brightness of modern displays and despite requiring minimal effort to implement, it still isn’t standard. With AI, vendors can configure the ‘last mile’ of the interface based on data collected and stored with an AI agent’s memory, which can include feedback on what tools or data points the user might need.
Consequences
The consequence of this, is that the AI is customizing the UI in ways that simply aren’t possible with traditional tools. Programs can respond to user level and environmental requirements, factors like time of day, colloquializations and adapting visualizations to account for data literacy. Imagine how much easier it would be to get things done if your sales platform knew when it was reporting season and reconfigured to highlight the KPIs you needed for a report. It is these smaller changes that save a few minutes each day and which in aggregate make a big difference.
‘Enterprise’ used to mean something that was better than the basic, consumer-facing option. Consumer apps have massively upped their level and now pro tools need to play catch up by offering something more sophisticated and elegant. Taking risks in integrating AI to interfaces and analytics will change the way we interact with computers, creating applications that are better than the old ones and delivering on the promise of enterprise grade tooling is the path to killing shadow IT.
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