Navigating the AI tools market

Haroen Vermylen at Luzmo explains how to choose the right AI solution for your business

 

The market for AI tools has evolved significantly over the past twelve months, moving beyond 2023’s widespread “AI everything” enthusiasm to a more nuanced perspective. 

 

While some companies remain cautious, others are accelerating their investments in foundational models, reaping advantages like improved performance and getting first access to new features.

 

This growing disparity underscores a critical trend: organisations heavily investing in automation and generative AI (Gen AI) are pulling ahead, while laggards risk falling further behind as the technology landscape continues to rapidly evolve.

 

As the product adoption curve has moved to encompass the early majority and for those who have bided their time, there is a blueprint for purchasing AI tools that will add value in proportion to its costs. Time is of the essence in this case, with early adopters intending to outspend late adopters three to one to capitalise on these efficiencies.

 

The truth is, AI is capable of tackling almost any task, but that doesn’t mean it’s always the right tool for the job. Successful AI adoption requires careful consideration of where it can deliver the most value, rather than trying to apply it to every possible use case.

 

Keep it focused

When planning the first implementation of AI, approach it as a strategic initiative rather than a narrow pilot. Focusing on specific, high-impact areas such as automating repetitive tasks or uncovering insights from data can quickly deliver a return on AI investments but instead of isolating small, department-specific automation tasks, set bold, cross-functional goals that align with broader business priorities.

 

This is the balancing act for firms trying to invest in AI, finding use cases with wide reaching strategic implications but with a scope that can be implemented in a short time frame. 

 

This means identifying tasks that are often highly-resource intensive and laborious despite their clear contribution to productivity, and then embedding AI efforts to automate these tasks with the company’s strategic agenda.

 

Doing so ensures executive sponsorship and fosters alignment across departments, paving the way for AI to become a pillar of an organisation’s long-term transformation and avoids the pitfalls of overcomplicating or misdirecting AI projects. 

 

One clear example is finding insights from data. There are so many potential hypotheses to explore that it can be overwhelming and lead to firms running the same studies repeatedly, even if the existing trends are already well understood. This is the definition of wasted effort.

 

AI can help with surfacing novel trends which offer new avenues for creating a competitive advantage. They can also automate existing analyses that teams rely on as their ‘bread and butter’ for understanding markets and buyer behaviour.

 

Salespeople and administrators are constantly combing through information to find a signal or insight in the information that will prompt activity. A smart AI analyst can either exist within a dashboard and help the user navigate or adapt it, or connect directly with your databases and find insights autonomously. This closes the gap between recognising a problem, finding a solution and acting on it.

 

Be clear about the problem(s) you are solving

In the early stages of any deployment it is advisable not to involve too many stakeholders. Obviously, if it is a sales tool, the technical and sales departments need to be consulted, but the potential of AI means that every department will have a use case for AI. This can pull a project off track as a proposal gets diluted by trying to achieve too much at once.

 

For a first integration, keep things simple, identify the problem(s) you are trying to solve and the rest will follow. The learnings from this initial project will make creating something that can serve other areas of the business even easier.

 

Given that AI has now evolved far beyond simply being a chat window, when considering the problems that can be solved, the net can now be cast wider. Developments in areas like agentic AI - essentially a virtual assistant that can think, reason and adapt to changing circumstances without needing constant human direction - means that it is now possible for AI tools to automate tasks such as scanning the web overnight and send reports summarising events first thing in the morning. 

 

From a business standpoint, the productivity gains from automating the arduous task of gathering insights, analysing statistics and creating graphics and graphs to make insights easily digestible are huge. Once you have an idea of your needs and cost constraints, the boundaries for creativity and problem solving can be drawn. 

 

Choose something embeddable

AI apps often exist outside of the software where work takes place, which can be a stumbling block for deployment. AI developers have attempted to address this early on by offering co-pilots within software, with Microsoft and Google having led the way by embedding this functionality into their platforms. 

 

However, opting for one of these solutions locks you into that ecosystem. Many vendors now offer embeddable AI tools which exist within a workflow and consequently can be added to sales dashboards, inventory management systems and vehicle fleet management solutions.

 

Embedding solutions like this helps to reduce friction for users and will increase uptake. As we know, AI can be an expensive investment and having it go unused is all too common, so think about how you will get the software into the hands of those it is supposed to benefit.

 

Ultimately, selecting and rolling out an AI integration might seem daunting at first, but it’s just software, and the upsides are obvious. Businesses shouldn’t have AI anxiety any more than Excel or Powerpoint anxiety. It is just another tool that can make you better at what you already do.

 

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Haroen Vermylen is Co-founder and CTO of Luzmo 

 

Main image courtesy of iStockPhoto.com and sankai