Technology 3 top tips to help SMBs make a successful...

3 top tips to help SMBs make a successful home in the AI ​​space


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Three things are certain in life: death, taxes and artificial intelligence (AI). Not only is AI significantly less depressing than the other two, it has spawned a number of business innovations and is becoming increasingly affordable as a mass solution. In the startup space, AI has helped predict trends in Covid variants, power military tools and prevent physician burnout.

In addition to AI’s “sexier” applications, the technology has boomed in a sector that literally defines everyday life: logistics. Here, AI has optimized delivery routes, shortened last-mile delivery times, driven sustainable measures, and reduced operational costs. I know this firsthand because I designed the AI ​​for my logistics startup after initially creating an algorithm for my master’s thesis that planned routes for firefighters. This algorithm saved 1,400 lives and reduced time to arrival in some of the world’s busiest cities by 40%.

The benefits of AI are undeniable. However, companies often shy away from fully committing to it because they think it is too complex or too expensive to integrate. Of course, in the face of today’s volatile market, companies need to double their efficiency, but it’s still possible to embrace AI and not send shockwaves to your accounting department. With that in mind, these are my tips for small and medium-sized businesses (SMBs) looking to put their last mile in the AI ​​world and make it a home for the long haul.

SMB: Make sure your fundamentals are good for AI

It sounds obvious, but every company must first establish its real need for AI before it becomes a permanent part of its model. In the last mile, this means asking yourself if your customers want personalized delivery, for example if they want to be able to choose when they receive goods, or if they are happy with more standardized processes. If there is no demand for nuanced delivery, AI may not be the right route for you, as AI’s specialty lies in its ability to accommodate multiple disparate outcomes.


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Next, look at your customers’ behavior and expectations. Do they change daily or are they generally consistent? If their preferences are fixed (when and how they receive deliveries, for example, they stay the same), AI won’t be as beneficial to your business. AI is valuable for detecting and understanding patterns in datasets, so if you already have a clear understanding of your customers, AI cannot tell you anything new.

For the final sensory check, turn to your existing technology. If you don’t have intelligence software to begin with, skipping over to AI could get you in trouble. Ideally, you need some automated, smart processes so that you can scale them using AI. Remember AI is not the end result, it should be an accelerator of your pre-aligned practices.

Most SMBs will choose to use AI through third-party tools, which makes sense since building your own AI from scratch essentially means becoming a software company. That said, even if you’re using other people’s AI, you’ll need to put together a team to manage the technology. . The more technical your team is, the faster and more seamlessly you can integrate AI.

Create a toolbox to cultivate your AI

AI is not a “set and forget” solution; you need a comprehensive toolbox to drive and measure effectiveness from day one. Fortunately, due to AI’s prominence in business, there are plenty of tools to keep your AI in check.

Let’s start with the basics. Over the past decade, the most common elements of AI have been packaged and made more accessible to a range of industries. One of the most popular AI tools is TensorFlow which is great for bundling and building AI – the main open source library helps train machine learning models and can run right in your web browser. In the meantime, Python is a widely used AI programming language, and R helps data scientists scale and align with different AI models.

Elsewhere, Google’s ML kit is useful if you want to form your own AI offering. And communities like Hugging face are ideal for researching AI and participating in conversations around it.

In addition to these tools, make sure you regularly collect feedback from the real people using the AI. Be sure to recalibrate the algorithms accordingly. It’s all well and good to have the tools to fix a car, but if you don’t know how to use them to accommodate the driver, they are of little value. At SimpliRoute, we ask all our delivery staff to rate the routes our AI recommends to them on a scale of 1 to 5. This quantitative information is then used in conjunction with qualitative data (such as surveys) to better identify what does and works not with the AI.

Prepare data to be your long-term AI power supply

Becoming an AI company means entering into a long-term relationship. AI won’t serve your SMB or your users if it stagnates – it needs to be dynamic, combining historical and real-time data to generate insights. Therefore, about 80% of your last mile spend will shift to collecting, retrieving and fixing the data that powers your AI and keeps those insights coming.

However, data needs maintenance. You must constantly pull data from multiple sources to ensure you have the fullest possible picture of your last-mile operations. For example, we need a lot of GPS data, but also service information about the time it takes to unload trucks and what the drivers’ preferred routes are. You cannot select the data that confirms what you already know (or want to know). Your data needs to be truly representative for your AI to be most effective.

Invest not only in data sources, but also in data people. You will need training on emerging AI trends and models for current staff, as well as any new members you bring on to manage AI. If you’re hoping to grow your AI team, partner with universities to attract cutting-edge talent, or offer internships that show why your AI application is unique, a mix of the business and academia can work wonders for your AI status.

At the same time, data should not only be kept in the departments where AI plays a role, but should influence decisions around the world. whole company, in your marketing teams, sales funnels and more. If data isn’t at the center of all decision-making, you’re never really stepping into your end-users’ shoes and can more accurately determine what to do with the conclusions your AI gives you.

Embracing AI doesn’t have to be an almighty hill to climb. With so many companies successfully carving out their niche in the AI ​​landscape and so many resources to facilitate the ventures of new entrants into it, SMBs are better prepared than ever to become an AI authority.

Alvaro Echeverria is founder and CEO of SimpliRouteroute optimization software that helps companies reduce logistics costs and increase customer satisfaction.

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