Biological organizations offering products and services, especially in the medical industry, are beginning to rely on AI (artificial intelligence) to raise their performance efficiency. Respondents of a McKinsey 2020 survey stated that their revenue increased from 60% to 80% after their marketing, sales, and service operations departments adopted AI practices.

Higher-performing AI users credited their greater efficiency and effectiveness to the execution of well-designed strategies for the adoption of the technology. A very important factor was hiring highly qualified personnel for overseeing the implementation and management of AI solutions. Others credited properly providing the most up-to-date data to AI programs, optimizing their capacities.

Advantages and Disadvantages of AI

A significant advantage of the adoption of AI programs is the ability to customize them for the individual requirements of an organization. An environmental systems lab will have many different needs for data and production than a medical research company.

AI lets a laboratory carry out customization to meet its organization’s particular requirements for computing, data management, and storage. An organization deploying AI typically prefers to train its own IT technicians for implementation, management, and maintenance, rather than hiring costlier consultants.

There may be a disadvantage for life science companies stemming from the risks involved in empowering AI-based systems to oversee production. Cybersecurity, privacy protection, and regulatory compliance are the main concerns when utilizing AI solutions.  

Taking these three risks appears to place biological organizations in two diametrically opposed positions regarding working with AI. The first is willing to accept risks and mitigate them. The second is being uncomfortable about the risks and choosing not to go forward with the technology.

What has been found by companies deciding on the implementation of AI solutions is that the advantages have outweighed the disadvantages. However, adequate time and resources need to be committed for proper planning, training, deployment, and upkeep.

Part 2 will discuss Levels of AI and Advanced Machine Learning.

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