How to integrate gen AI into your business operations

Do you leverage generative AI tools in your business operations? 麦肯锡 calls 2023 a “generative AI’s breakout year”. According to their global survey, one-third of respondents indicate that their organizations are currently incorporating generative AI regularly in at least one function. Which implies that 60% of organizations reporting AI adoption are utilizing generative AI, with an additional 28% who note that the use of generative AI is already on their board's agenda.

If you are considering exploring and incorporating generative AI tools into business processes, it is crucial to create a secure environment:

Have Clarity

The power and potential of generative AI is nothing we have seen before. If you are planning to integrate it in your daily business processes, you need to be clear about your goals. Do you need AI to help your organization with data processing and interpretation? Do you want your marketing department to have more tools for content creation? Set your goals, align them with the overall business strategy and have a clear idea of how gen AI will fit into it.

Ensure Data Accuracy

The content generative AI model produces may often look extremely convincing. But sometimes the information it generates is simply wrong, make sure to fact check.

Mitigate the Ethical Concerns

The output generated by the AI can be biased, unethical, offensive or it can even encourage criminal activity (don’t ask me how I know that). After all AI algorithm replicates patterns, it sources from the open web, and the internet itself is biased. Organizations that rely on generative AI models should reckon with reputational and legal risks involved in unintentionally publishing unethical or copyrighted content. Make sure to establish clear ethical principles for AI use within the organization.

Stay Compliant

Understand and comply with the regulations and standards governing the use of AI in the region and industry you operate in. Stay informed about changes in legislation related to data privacy and AI.

Assess Risks

Conduct a thorough risk assessment to identify potential risks associated with generative AI implementation. Develop strategies, internal processes, and SOPs to mitigate and manage these risks effectively.

Ensure Data Safety and Security

It is important to have clear guidelines in regards to data input (we all remember the Samsung’s code leak incident) as well as to implement robust security measures to protect AI systems from cyber threats, unauthorized access, and data breaches. Implement encryption, access controls, and regular security audits.

Provide Training

Before, most new tools were quite easy to implement, and they only enabled us to perform tasks more efficiently. Generative AI is completely different: it’s a system you need to learn and train that could in return provide insights, analysis, research, etc. Therefore, it is important to have clear and detailed internal AI guidelines and provide training to ensure that your employees can understand the technology and effectively utilize it. Encourage collaboration between different departments such as IT, marketing, legal, etc. – a multidisciplinary approach will ensure a holistic understanding and implementation of the tools. Keep in mind, AI implementation is not going to be a one-time thing, it will require continuous adaptation to changes.

Monitor

Establish mechanisms for continuous monitoring and evaluation of gen AI performance. Regularly assess the impact on business processes and make adjustments as needed.

A quick start has its merits, but business leaders should always consider the risk factors. Making sure your organization is ready and that you have a safe and secure infrastructure prior to incorporating AI will empower your business to be more effective in its generative AI journey.