Four Aspects Companies Must Emphasis on Before Adopting AI

Check out 4 aspects that every company must take care of before adopting AI.

Adopting AI

Adopting AI

Artificial intelligence and machine learning have become the most important part of our daily lives. Smart speakers, facial recognition, voice recognition, smart voice assistant, etc are AI-powered technologies that are being used daily. Inside a company, AI holds a different position where it benefits a wide range of cases such as automation, supply chain, efficient production, intelligent cybersecurity, etc. Therefore the scale of adopting AI is more in companies, industries, and businesses. 

In the 700 IT pros survey, 95% of the companies responded that they benefit from the implementation of AI-driven tools into daily operations, products, and services. Other than this 88% is emphasizing using AI as much as possible. 

Along with these, AI is a way for IT workers to help them in doing their tasks more quickly and efficiently. Just like consumers have moved towards the daily use of smart assistants and smart speakers, in a similar way the IT workers are moving towards the use of AI daily. Conversations with CIOs indicated that the C-suite of every company faces numerous technical, organizational challenges in coping up with AI. 

The prediction made by IDC showed that the revenues across the globe for the AI market which includes software and hardware services will rise 16.4% this year to $327.5B and will break the $500B streak by 2024. Much of such growth will come from business enterprises because of broader AI adoption. 

Adoption of AI is not that difficult but moving forward with it is what makes it critical and complex.  Every company must emphasize four things before adopting AI.


Focus and intention 

A company must understand its intention of adopting AI because AI is not something that can be treated as just another t-do-list. AI needs more prior attention than any other thing. AI needs adequate funding and also, the company has to acquire the smartest people to optimize AI. undoubtedly the CIOs play an important role but many challenges are revolving around AI that the CIOS alone can’t deal with. It requires the top executives which include the CEO and other critical executives to take the company towards AI for efficient production.


Data challenges

A company must realize and understand whether it is capable enough to cope up with data challenges. To hold the grip of technology up-gradation which is required for AI is one of the most challenging hurdles in AI adoption. The IDC report has showcased a lot more spendings made by business enterprises on data integration and data preparation than on actual data science efforts which inhibits the scaling of AI adoption. Therefore it is important to understand and realize the priority and resolve challenges otherwise adopting AI can be problematic. The need for the right infrastructure for centralizing and adopting AI must be acknowledged by every company before adopting AI.


Improved Workforce 

Companies need to ensure that there is enough workforce with enhanced skills to support aI and go hand in hand with it. Many IT workers are led by creative thinking and problem-solving and want to move out from their daily routine work to something creative. The adoption of AI will help in unlocking those creative minds. Thus, AI will not only make life easier for IT workers but also enhance the efficiency of all employees. But along with this, some workers are capable of performing routine work only. For them, AI can be a threat as they might lose their jobs. But it is the work of the company to train those workers to get accustomed to AI and to move forward with it.


Governance and Security

Before adopting or deploying AI, a company needs to focus on the operational, reputational, and financial risk that is associated with AI. A company must ensure whether adopting AI will meet its own business and ethical standards. It should also take into consideration the government regulations before adopting AI. 

Source code Repositories in standard software development are secured but the data used in AI models are outside the work system and require unique consideration. This exhibits that companies must broaden their security strategies and practices to account for the uniqueness of AI development.

By emphasizing all the above aspects, a company can easily adopt AI and enjoy the benefit of the most advanced technologies. 


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