5 Tips to Help Business Leaders Make Sense of the AI Landscape | Entrepreneur

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It’s become more and more common to be in a meeting and hear someone say, “What’s our AI strategy?” Top-level executives and management have been planning on this for some time, and it’s probably time to carry it out or risk being left behind.

According to Statista, revenue from the artificial intelligence (AI) software market worldwide is expected to reach U.S. $126B by 2025.

As per Gartner, 37% of organizations have implemented AI in some form. Also, the percentage of enterprises employing AI grew 270% over the past four years.

As the technology gets adopted in more industries, it grows in its use cases; Generative AI alone now includes visual media, generative interfaces, text, speech, audio and code.

However, with so many different types of AI technologies and companies emerging all the time, it can be difficult to make sense of it all. So, here are five key tips to help you get started with integrating AI solutions.

1. Start by understanding the technology

There are different types of AI technologies, each with its own purposes.

Machine learning (ML):  ML is a type of AI that allows computers to learn without being explicitly programmed. ML algorithms are trained on large datasets and then use that data to make predictions or decisions. Examples of how companies are using ML today are Netflix and Amazon. They ingest the large dataset of their customers’ behavior, searches and selections to make recommendations.
Deep learning (DL):  DL is a type of ML that uses artificial neural networks to learn from data. Neural networks are inspired by the structure of the human brain, and they are able to learn complex patterns from data. A company would use deep learning when it needs to solve a problem that is complex or requires a high degree of accuracy such as identifying objects and scenes in images and videos, generating chatbots or detecting fraud.
Natural language processing (NLP): NLP is a type of AI that allows computers to understand and process human language. NLP algorithms can be used for tasks such as machine translation, text summarization and question answering. It is used to analyze social media posts, customer reviews, customer feedback and sales data.
Computer vision (CV): CV is a type of AI that allows computers to understand and process images and videos. CV algorithms can be used for tasks such as object detection, facial recognition and image classification. Computer vision models can be used to inspect products for defects and ensure that they meet quality standards. This technology is used in a variety of industries, such as manufacturing, food processing and pharmaceuticals, as well as surveillance and fraud detection.

2. Identify your needs

What are you trying to achieve with AI? Once you know your needs, you can start to narrow down the range of AI technologies and companies that are relevant to you. One of the earliest adoptions is being seen in ecommerce and finding ways to improve the customer experience. Also, more than half of the companies surveyed by AI Infrastructure indicated that they would augment their existing AI/ML teams with more data scientists, data engineers and DevOps.

3. Evaluate different AI companies

Look for companies that have a good track record of developing and deploying AI technologies. Consider the company’s expertise in the specific AI technologies that you are interested in.

4. Evaluate success stories and use cases

Here are a few examples of how AI is being used in the business world today:

Customer service:  AI chatbots are being used to provide customer service 24/7. Chatbots can answer customer questions, resolve customer issues and even make recommendations to customers.
Sales and marketing:  AI is being used to improve sales and marketing efforts. AI algorithms can be used to identify and target potential customers, personalize marketing messages and predict customer churn.
Product development:  AI is being used to develop new products and services. AI algorithms can be used to analyze customer data, identify customer needs and generate new product ideas.
Manufacturing and operations:  AI is being used to improve manufacturing and operations processes. AI algorithms can be used to optimize production schedules, predict equipment failures and identify quality control issues.

5. Start small

Don’t try to implement a complex AI solution right away. Start by implementing a simple AI solution that can solve a specific problem for you. Once you have a successful implementation, you can gradually scale up your AI efforts.

AI is a powerful technology with the potential to transform our world. By understanding the different types of AI technologies and companies that are available, you can start to leverage AI to achieve your business goals.

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