AI Projects: 5 Tips On How Companies Can Make Better Use Of AI

AI Projects: The use of artificial intelligence brings many advantages for companies. However, we will only reach their full potential. Artificial intelligence in companies and machine learning (ML)? In April 2019, IDC examined the current status of this technology in the study “Artificial Intelligence in 2019”. 

AI Projects: Five Recommendations For Successful AI Projects In Companies

Algorithms, robots, and digital assistants have long since found their way into companies – and will be used even more frequently in the future. A good 40 percent of companies have already worked with artificial intelligence (AI), and 88 percent plan to do so in the next twelve months. These are the results of the IDC study “Artificial Intelligence in 2019”, in which decision-makers from 305 companies were surveyed in April 2019.

With the help of AI, the companies want to automate processes in IT (34 percent) as well as in sales and marketing (31 percent) and optimize personnel deployment (30 percent). They named these three business goals the most frequently. Companies use AI primarily for process optimization – and thus do not fully exploit their potential. Because not even a third of the respondents stated that they wanted to drive innovations with AI projects. Every company has it in its own hands to use the algorithms for its entrepreneurial advantage. You can do this if you adhere to the following five recommendations:

Define Realistic Business Cases For AI Projects

If companies want to tackle AI projects successfully, they should be clearly defined and achieve a clear business benefit. However, 47 percent of the companies surveyed find it difficult to define suitable use cases for themselves. It is also particularly challenging for more than half of the respondents to introduce an AI model and qualify the necessary data. Companies master these challenges when they compare the technical requirements with the technological possibilities in the company. For users with little experience, it is advisable to start with simple and non-critical projects and, if necessary, to call in external help. Then AI can be used in various ways, for example, for tests and simulations in production.

Artificial Intelligence In Companies: Optimize Data Quality And Evaluate A Data Platform

AI analyzes existing data and enables companies to optimize existing processes and create new ones. In addition, the collected data can be used to gain comprehensive insights into the markets, products, and customers. The selection of the relevant data and high data quality is crucial for the success of AI initiatives. The management of the information should be automated as much as possible. Because manual administration is complex, time-consuming, and not very clear. However, companies still have a lot of catching up to do here: According to the IDC study, only 17 percent have automated processes for data provision so far. You gain efficiency and transparency with a data management platform. This should be able to process different data and formats,

Start AI Projects With Application Scenarios

Which AI project will be implemented first? Companies are often faced with this question. Projects based on pattern recognition or process automation can be implemented quickly and lead to results quickly. Robotic Process Automation (RPA), for example, has proven to be a good start. This technology makes processes in the

Companies are more efficient, error-free, and more transparent. It is ideal for simple and repetitive processes in the IT department, accounting, or customer service, among other things. Half of the companies surveyed already use RPA. Other entry scenarios also include chatbots and solutions for predictive maintenance. Among the AI ​​functionalities used, text pattern, speech, and image recognition are used most frequently 

Check Deployment Models For AI Projects

Users can use AI platforms and services locally as on-premises solutions or in the cloud. According to the IDC study, 43 percent of the companies surveyed prefer the private cloud in their own data center to operate their AI platform. They particularly appreciate this model’s greater flexibility than a purely local solution and the feeling of having more data security than in a public cloud. Overall, more than half of the companies surveyed use cloud-based AI services (61 percent). And for a good reason: Because the cloud offers you an uncomplicated, needs-based provision of IT resources. However, the business case should determine the choice of technology, not the other way around. Because it is also important for companies: AI always requires coordinated hardware and software. Users with little experience should therefore seek external specialist knowledge.

Build Up Knowledge Of Artificial Intelligence

But as much as many companies want to implement AI projects, most of them are confronted with a common problem: the acute shortage of skilled workers. Well over half of them state that a lack of specialist staff is the cause of the failure of AI projects. For example, they lack developers for AI systems or data scientists – a situation that is unlikely to change, at least in the short term. But there are ways and possibilities for companies to build up AI knowledge in-house: For example, they can train their specialists, form AI working groups, or cooperate with universities and start-ups. The following applies: AI projects are most successful when specialist departments and IT cooperate closely with one another from the start.

companies are already making profitable use of artificial intelligence. Go one step further and establish an AI culture in your company. Over the next few years, you can benefit from the developments and opportunities offered by the technology, such as higher computing power, more data, and better algorithms. Because artificial intelligence brings more than just improved business processes: It releases creativity, models ideas, and accelerates innovations.

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