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Analysts are projecting severe transformations. Whole industries will be disrupted or rendered redundant. Tens of millions of roles will be redesigned or phased out. And only businesses that smartly leverage AI will come through unscathed. If you’d like your company to survive the coming Artificial Intelligence revolution (and thrive on it), here are six steps you should take:
Identify the Areas Where AI Can Be Applied
The first step in preparing for Artificial Intelligence is to conduct an audit of your operations and identify areas for application. You will need a decent knowledge of the technology and its potential if you’re going to get this right. Ask your tech team (or some well-informed professional) to help out. Start by analyzing the processes that can be automated and the data that can be analyzed to gain insights. For example, AI can be used in customer service to provide personalized recommendations or in marketing to optimize ad targeting.Invest in Data Management
AI relies on data to function, so it is essential to invest in data management. You will have to collect and store data in a structured way that can be easily accessed and probed. Also, ensure that the data is accurate and up-to-date. If you’re careful enough about how you invest in data management, you’ll ensure that your business has the right data to train its AI systems.Train Employees to Use AI Technology
Many businesses will eventually have to change their structure in order to adapt to a world in which AI is dominant. They may have to bring in persons who are skilled at managing the technology, or trim roles that can be almost totally handled by it. But you will also have to train existing employees to use AI technology effectively. They’ll need to acquire and sharpen skills in data management, machine learning algorithms, and AI software utilization. It is also essential to educate employees on the potential impact of AI on their jobs.Sign up for the Connect Nigeria daily newsletter
Develop an AI Strategy
It’s important that you have a deliberate strategy for riding the waves of the AI revolution. Set goals and objectives for AI implementation, identify the resources you’ll need to start and maintain processes and develop a timeline for implementation. An AI strategy should also consider the potential risks and challenges associated with AI, such as data privacy and ethical concerns. These issues will loom large in the public’s consciousness as the technology matures and becomes more widely used.Collaborate with AI Vendors
You can benefit from collaborating with AI vendors who provide expertise and resources to implement AI. The best of these firms will supply you with fully-baked AI-specific or AI-enhanced products that deliver lower operational costs and higher ROI. They can help you with data management, AI software tools, and machine learning algorithms. You may also rely on them to train and support your employees.Monitor and Adapt
AI technology is constantly evolving, so you should monitor the relevant trends and adapt accordingly. Regularly evaluate the performance of AI systems and make changes when and where they’re needed. At the moment, Artificial Intelligence is gaining in capability and potential use cases at a pace that’s hard to keep up with. But putting in the effort to stay in touch with it will be worth it eventually.Register to attend the CN Business Mixer
Final Words
As was the case with previous large-scale changes in technology, the coming of age of Artificial Intelligence will deliver benefits and pose challenges. Only the prepared will thrive with it. Be one of them; take the steps we’ve talked about here, and get ready to excel in tomorrow’s brave new world. Featured Image Source: Tech News WorldGot a suggestion? Contact us: editor@connectnigeria.com
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To establish an AI, you must first determine the issue you’re attempting to solve, gather the necessary data, develop algorithms, train the AI model, select the appropriate platform, and select a programming language.
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Unquestionably, the most crucial phase of the AI workflow is data preparation. Projects have a higher chance of failing if the data used to train the model is not reliable and accurate.
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