Leveraging Generative AI in Business: Risks and Rewards

Leveraging Generative AI in Business: Risks and Rewards

Leveraging Generative AI in Business: Risks and Rewards

Artificial Intelligence (AI) has made remarkable strides in the past year, with generative AI standing as one of the most intriguing developments. However, as promising as this technology is, it’s not without its risks. Companies considering the adoption of generative AI should first understand these potential pitfalls.


Firstly, generative AI operates on the principle of learning from very large datasets, then concocting new content based on that information. One critical issue is that the new content generated is not guaranteed to be factual. The internal workings of generative models do not generate factual information. Users must be aware of the risk of hallucinations .

Secondly, the quality of the output from generative AI is entirely dependent on the quality of the user prompt. Untrained users will not get the full benefit of the technology and may lose interest quickly. Just chatting with a generative AI may lead to more time wasted than time gained.

Thirdly, there is a natural human tendency to anthropomorphize machines. With perfect text and images generated by this new technology, users may be tempted to see intent, creativity, and emotions where there is only code and statistics. It is important to treat generative AI as tools, here to help us.


Despite these risks, the productivity gains from generative AI are substantial enough to warrant serious consideration. One of the main advantages lies in its capacity for acceleration and automation. Generative AI can manipulate unstructured data at a pace no human can match, freeing up employees to focus on more complex, strategic tasks. This not only enhances efficiency but also reduces the likelihood of human error in repetitive tasks.

Additionally, generative AI can provide valuable insights that can be leveraged for strategic decision making. It can analyze vast amounts of data, identify patterns and trends, and summarize. This capacity for data-driven decision making can give companies a competitive edge in the market.

Furthermore, the versatility of generative AI is another significant productivity gain. It finds application across various business functions, from marketing, to human resources, research & development, IT, legal, strategy, operations. For more details, you can register to our list of use cases .

Rewards witout the risks

The key to harnessing the productivity gains of generative AI while mitigating its risks lies in a robust AI transformation methodology. This involves:

  • training users , to ensure that they reap benefits from using the technology right away,
  • providing them with as many use cases as possible , so they can reinforce and apply their learnings every day,
  • allowing them to build their own workflows, to chain AI tools, and further increase their productivity.

Moreover, SiM continues to develop and actively release new productivity tools, as part of its AI in Motion offering. New features are constantly being released, based on user feedback, new AI capabilities available, and a roadmap towards higher and higher performance.

In conclusion, generative AI indeed presents certain risks, such as hallucinations, user errors, and anthropomorphism. But its benefits, in terms of productivity gains from acceleration, automation, and versatility, are substantial. By implementing a robust AI transformation strategy, businesses can effectively harness the power of generative AI, realizing its benefits while also mitigating its risks.


In this era of digital transformation, companies that can adeptly navigate the balance between risk and reward will stand at the forefront of their industries. Indeed, generative AI, tempered with a solid SiM approach, can be a potent tool in a company’s arsenal, driving innovation, efficiency, and ultimately, success.

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