Thinking Forward with AI

Thinking Forward with AI

Lixar I.T. Tech

At Lixar, we believe in a human-in-the-loop approach to AI, which means we seek to uncover ways in which AI can help people live better, work better, and accomplish tasks more efficiently. This is increasingly valuable in a time when COVID-19 has upended the way we complete so many of our daily activities, and has especially impacted the way we work. 

Various industries have been hit with unprecedented losses, while others have seen a spike in demand that they are struggling to meet. The pandemic constitutes an extreme event for which none of us were prepared. However, businesses that had already integrated advanced analytics and AI into their operations were better positioned to adapt to the quickly changing market. That’s because these technologies offer advantages such as the ability to:

  • Get real-time data
  • Test outcomes for various scenarios
  • Make accurate predictions
  • Automate processes
  • Optimize schedules and assets

AI is a powerful tool to have in your kit. In the short term, you can find efficiencies that will allow you to stay afloat through a challenging time. In the long term, you can drive innovation that will improve the way you work and help you achieve your goals, while continuously solving new business challenges. After all, at their core, AI systems are problem-solving engines.

What is AI? 

Let’s begin at the beginning. If you are new to data analytics, you may be wondering, what exactly is AI? Because AI is a broad concept, it is sometimes difficult to define. In its most concise terms: AI, or Artificial Intelligence, is a data-driven machine, engineered to mimic human intelligence insofar as its ability to learn, adapt, problem solve, and make decisions. 

At this point, perhaps images from futuristic sci-fi movies leap to mind, but in reality, most of us are already interacting with AI on a regular basis. For example, next word suggestions that pop up on your screen as you type is a form of predictive AI. Those words are suggested based on patterns discerned from historical data — when it comes to AI, data is key.

An AI’s knowledge comes entirely from input data. The richer the data, the more sophisticated the AI. Unlike humans, machines are not subjective, as they are not sentient entities. Instead, all of the choices they make are based on data, and data alone. It is our responsibility as the people engineering the machines, to ensure that we are using relevant, current, and reliable data, without known biases. 

This may sound like an arduous undertaking, but it doesn’t have to be. Next, let’s take a look at a few practical tips for getting started.

Practical Ways to Get Started

No matter where you are in your data journey, or where you fall on the data maturity spectrum,  we have a few tips that will help you make the most out of your current situation, and get you AI-ready.

Data Discovery

A Data Discovery workshop allows you to assess where you are, what you have, and how to get where you want to be. 

First, identify your business drivers with a focus on the future. This includes your current business environment, your decision-making process, and your most pressing business challenges. Think ahead. Where do you want to be in five years, and what may inhibit you from getting there?

Next, take stock of your data inventory. Maybe you already use some analytics, maybe you’ve gone fully digital, maybe you still rely on local spreadsheets. In any case, it’s key to know what you have so that you can make sure it’s working for you. Take stock of your data flow and process, your approach to governance and curation, and any risks and dependencies, such as SLA agreements or external data suppliers.

Finally, put together a data strategy that will act as a roadmap for how your data inventory can help accelerate your business drivers and better position you for the future.

Data Pipeline

Before you can put your data strategy into action, you’ll need a data pipeline that is  designed to meet your specific business needs. Ideally, such a pipeline solution should:

  • Use flexible and scalable infrastructure
  • Have the ability to engineer high volumes of data from various sources
  • Offer near real-time analytics that are readily accessible
  • Be cost-effective

It’s the pipeline’s job to ingest your data so that it can be cleaned, curated, and modeled into meaningful analytics that you can easily interact with. However, the pipeline depends on having a well-orchestrated data model behind it that is designed to take in only relevant data, at exactly the right time. Strong DevOps is essential.

Test a Single Outcome

Once you have a data strategy in place and a data pipeline up and running, the best way to see proof of the benefits of being data-driven is to test a single outcome. For example, a business that requires certain weather conditions in order to operate efficiently, may want to start with a predictive model for weather forecasting that is more accurate than existing methods. Or, a business that relies on manual collection of large quantities of data may want to build a rule-based classification model that will automatically collect relevant data from a variety of sources. Implementing AI in either of these use cases means having an incredibly sophisticated level of predictive power and automation, fueled by real-time analytics. Innovation is about efficiency: doing more with less, and always being prepared for what may come next.

How HeroPath Can Help

Getting AI-ready means being truly data-driven, and Lixar has over 20 years of experience getting our partners there. Not only do we offer personalized data discovery workshops, but we have combined our experience and our Azure expertise to offer HeroPath, a fully managed, modern data platform that optimizes every step of your data journey, using best-in-class Microsoft components, that can be customized to meet your specific business needs. 

Our unique approach ensures that we understand your goals and help you achieve them by: 1) ingesting the right data; 2) transforming it using the right storage, AI-modeling and testing components, and 3) allowing  you to engage with it through interactive visualizations. 

HeroPath is an effective way to get AI-ready, in just weeks. At Lixar, we believe in building AI that enables people, that is designed for inclusivity, and that builds trust in technology. You can read more about our approach to ethical AI here

We know that these are unprecedented times, and ensuring your business has what it needs to weather the storm is critical. Data and AI solutions can help.

For more information, please contact us at