Artificial intelligence and machine learning are changing the way businesses operate. These technologies lead to inevitable and existential disruptions, but they also present profound new opportunities for innovation. According to a recent IDC Spending Guide, “spending on AI in the United States will grow to $120 billion by 2025, at the rate of 20% or more”, as companies realize the value of these advanced technologies and the need for them to remain relevant and to ensure growth in competitive industries.
As we move into a world where machines can learn from and interact with humans more effortlessly, the role of AI and ML in business is becoming more critical than ever before. These technologies are already present in many industries, from healthcare to manufacturing to financial services. They are also present in products like cars, smartphones, and in-the-home devices like Alexa, etc., which means these devices impact our everyday lives.
And as these technologies become more widely available, they’ll continue transforming businesses—and not everyone will be ready for it. But for those who embrace this change, incredible opportunities lie ahead.
How to get started
You’re not alone. AI and ML are rapidly changing how businesses operate, and it’s becoming more important than ever for companies to understand how these technologies can help them grow. But what does it take to develop a successful AI/ML strategy, and what are some common pitfalls to avoid?
Here are three steps to help you get started:
- Technology & Tools: AI/ML tools can help businesses make sense of their data, but only if they know which technology and tools to use and how to use them. AI and ML have been around for a while, but they’re still relatively new to most organizations. That means that you need to start by setting up the right tools before you can get started on any kind of actual project.
- Machine Learning Platforms – These platforms provide data scientists and developers with tools to build, test and deploy machine learning models.
- Data Management Platforms – These platforms allow companies to collect data from multiple sources, store it in one place, process it, and make it available for analytics and advanced applications like machine learning.
- Natural Language Processing Tools – NLP tools allow users to analyze text documents, extract information from them, understand their context and create structured information from unstructured content (such as emails or social media posts).
- Data Visualization Tools – These tools enable users to visually explore large amounts of data. They can help them identify trends in their business more effectively than through traditional methods such as spreadsheets or reports alone by displaying information graphically so that it’s easier for humans to interpret rather than just looking at numbers. Humans often find grasping visual pictures much more effortless than analyzing and digesting raw numbers alone.
- Workforce: Once your technology and tools are ready, it’s time to think about your workforce. If you don’t already have anyone on staff with AI and ML skills, then it might be time for some training or new hiring! While many people think there aren’t enough qualified workers with AI/ML skillsets, this isn’t necessarily true—there just aren’t enough workers with the right level of experience! It’s essential for companies to provide adequate training opportunities so that their employees can gain real-world skills that apply to their day-to-day workflows.
- Culture: Finally, culture is one of the most important parts of developing an effective AI/ML strategy. Your company’s culture is one of the most important factors when building AI and ML competencies. The culture determines how people in the company feel about the idea of artificial intelligence and machine learning and what they think are its benefits. It also affects whether or not they are willing to work with these technologies and if they will be able to use them effectively. To build a positive culture, you must ensure that all employees understand why your organization needs AI, what it can do for them, and how those benefits can help them achieve their goals. You also need to make sure that everyone understands how AI works, what their role is in using it, and what their responsibilities are in relation to using it correctly.
- Lack of Strategy – The first challenge in building AI and ML competencies in your organization is that it may not be clear what the AI strategy should be. This can lead to wasted time, resources, and effort if you don’t clearly know where you want to go. If you don’t have a plan, then it’s likely that you won’t be able to measure progress or evaluate whether or not you’re on track. This makes it harder to know when something needs to change or when something is working well enough that it’s time to move on to something else.
- Data: The most common challenge in building AI and ML competencies is the lack of data. A good AI system requires a material amount of training data, but it’s not always easy to obtain all of the necessary data.
- Technology & Talent: Another challenge is the lack of technology or tools to help you build your AI systems faster and more efficiently. Finding the right talent with the right skill set to build AI systems can also be challenging. This can be difficult because there aren’t vast pools of people who have experience in this area.
- Processes: Another challenge is figuring out how to build an efficient process for implementing new AI systems at your company so that you are successful from the beginning stages through implementation and beyond. This can be one of the trickiest parts because each organization often has its own unique processes involved with implementing new technologies, so it may take some time before you find one that works best for you!
Implementing AI and ML in your organization may look daunting, but it doesn’t need to be. All it takes is a good understanding of these capabilities and general use cases. Then comes determining the fit within your overall business strategy, followed by a sound plan and realistic timeline outlining the advanced technology integration into your ecosystem.
Look for help
If you want to leverage AI and ML within your organization and are looking for help to accelerate your plan, we can help you. We are a full-stack AI technology company that can partner with you to help you build a strong AI and ML competency within your business. Our team specializes in both fields, and we’ll work with you to develop solutions to help your business thrive in this digital age.
Intellect Data, Inc. is a software solutions company incorporating data science and artificial intelligence into modern digital products with Intellect2TM. IntellectDataTM develops and implements software, software components, and software as a service (SaaS) for enterprise, desktop, web, mobile, cloud, IoT, wearables, and AR/VR environments. Locate us on the web at www.intellectdata.com.