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Cut Through the Complexity Bloat by Adopting AI for Your Business

Bigger isn’t necessarily better. On an individual level, we can relate to that. Taking on a bigger responsibility, accepting a task that’s beyond your skill level, or attempting to do a challenge that’s too difficult, all of these can lead to failure. Not only is that unpleasant to deal with personally, but there can also be adverse consequences affecting others.

The same principle applies to businesses. Yet, entrepreneurs seem conditioned to ignore it. Growth is seen as a necessity. Complexity invariably comes with growth. If you don’t manage complexity, you become inefficient, indecisive, and unproductive as an organization. Ultimately, it prevents you from delivering value to your audience.

Can adding yet another layer, in the form of AI, actually help cut your operations’ complexity?

An exponential bloat

Most people struggle to fully grasp how quickly complexity bloat can grow. That has to do with its exponential nature. 

A simple system with two elements, represented by dots, can have only one connection. Three dots can connect three ways, forming a triangle. Four dots, six connections. So far, it’s simple enough to draw that on a scrap of paper.

But six elements connect in fifteen ways. Eight elements can form twenty-eight connections. It’s exponential growth, which our minds aren’t accustomed to dealing with.

When a landlord’s operations are running smoothly, they feel confident about expanding, using the revenue generated to purchase other properties to let. In their mind, they can expect to roughly multiply their passive income streams by however many properties and tenants they have.

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However, each property brings with it a whole host of connection points. There are multiple tasks associated with maintenance, such as having an EICR assessor conduct inspections or attending to repair jobs and tenant complaints. Each tenant relationship will also vary. Some might be more or less difficult than others. Travel distance can make it harder to oversee everything in person.

So the landlord hires assistants and establishes relationships with different letting agents in each area where they own property. Again, these are people, not machines. Their relationships bring added complications into the picture. Complexity grows, and if the landlord didn’t anticipate that and manage it, they might question if the whole expansion effort was really worthwhile.

The AI advantage in tech

Some businesses can dial up their operations without substantially increasing their complexity. They can take advantage of scaling effects to grow revenue without necessarily adding more elements.

This happens all the time among tech startups. The same team that develops a custom B2B software solution can modify it for a B2C market, for instance. They don’t need to hire additional personnel or buy new machinery.

Tech companies do enjoy an inherent advantage in working with virtual products and services. But that’s not always the case, nor does it fully explain how they can manage to scale so well without suffering complexity bloat. Their key edge comes from maximizing the potential of AI to manage complexity.

A multifunctional tool for specific problems

How can AI help even non-tech businesses to streamline their complexity?

Most business owners default to thinking about AI in the context of automation. They know that automation has been used across industries to eliminate human error. By taking time-consuming, repetitive tasks out of human hands, you can operate more efficiently.

The problem is that not all businesses are reliant on such tasks. So leaders struggle to identify other uses for AI.

Data analysis is among the most immediate use cases of AI for any business. It can facilitate the identification through machine learning, of which 20% of customers drive 80% of results, following the Pareto principle. Training the AI lens can also be used to spot internal inefficiencies to yield similar improvements.

Machine learning also allows AI to help increase an organization’s predictive capabilities. Algorithms can quickly detect suspicious anomalies in a data set. Calling attention to such outliers is one way in which you can thwart complexity-related catastrophic failures.

AI isn’t just capable of taking over tedious jobs. Natural language processing technology can help human users narrow the skill gap from novice to expert level in a variety of tasks. This makes employees more productive without requiring anywhere near the same level of time and training.

Organizations that aren’t filled with native tech users might resist adopting AI. After all, it’s yet another element. If you’re already burdened with complexity, that might be the last thing you want.

But this element has the potential to reduce complexity itself. It’s a multifunctional tool, so make sure you align it with a specific purpose, and you can start streamlining your operations.

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