The main challenges when integrating artificial intelligence (AI) into our companies

Personally, I find all changes difficult. Some experts call me "change averse." Perhaps it's based on a fear of letting go of habits that have worked for me so far, and also because change entails readjustment and, above all, makes me feel uncomfortable. However, over time, I've come to understand that you have to take risks because it's the only way to evolve.

As leaders within our companies, we must do everything possible to convey to our teams that it is important to change, re-adapt, and, as one of my clients said, we must constantly recalculate.

With all this AI hype, I'm certain we need to embrace change, and soon. But I must also admit it's stirred quite a few feelings in me. I'll share some with you; perhaps you're feeling something similar.

I'm afraid of being faced with something very powerful, the limits of which we all don't know.

I'm overcome with nostalgia for how we were raised. Countless theories, maps, authors, and formulas we had to memorize, and today we wonder, why?

I touch on the territory of anxiety when I see us living with the "anxious generation," fueled largely by the excessive use of technology. And now AI. What will our future hold?

I'm filled with joy, a feeling of happiness and intense positivity about how we can leverage all of this to become better and better, and for our businesses to grow as we dream of.

That said, the people who work in our organizations, just like us, have emotions about this whole AI issue, so we need to identify what they are in order to work on them and make it easier to integrate AI into our ways of working.

Here are some of the reactions I've gathered from what our clients and potential clients have told us as we're working to understand their pain points and how we can help them integrate AI into their industry workspaces:

1. Resistance to change and lack of understanding:

Many teams fear that AI will replace their roles or diminish their relevance, generating resistance. Furthermore, a lack of knowledge about what AI is, how it works, and its benefits limits their openness to even understanding it.

2. Data quality and management:

AI relies on accurate, complete, and up-to-date data to generate useful insights. However, many organizations struggle with disorganized or incomplete databases, which hinders the effectiveness of AI solutions. For teams, the usual response is that the data has always been that way, whether it worked or not, and now being told it's not the right way to go makes them irritable.

3. Integrate artificial intelligence with existing systems

Companies have platforms like intranets, CRM platforms, etc., and they find it incredibly complex to integrate them with AI solutions. They say it's better to keep everything the same, because all this AI stuff is sure to cost a lot of money.

4. Lack of transparency and explainability

AI models, especially those based on deep learning, often operate as "black boxes," making it difficult to understand how decisions or recommendations are made. This lack of transparency can lead to distrust among both teams and clients.

5. Costs and return on investment

Implementing AI can require a significant investment in technology, infrastructure, and talent. Many companies, especially SMEs, are hesitant to make this investment without a clear strategy and metrics to assess ROI.

6. Ethical concerns and privacy

Companies' handling of personal and private data poses privacy risks. Teams say they don't want to leave their confidential information in the hands of AI.

7. Continuous measurement and evaluation (especially for sales areas)

Determining the effectiveness and accuracy of AI models is complex. It can be difficult to determine metrics, and it's time-consuming to continually test and fine-tune solutions to ensure they deliver real sales value.

These are just a few of the insights I've found so far about integrating artificial intelligence . However, many are based on emotions like fear and uncertainty. But above all, due to a lack of knowledge. Each of these points has some merit, but we must educate ourselves, inform ourselves, and seek advice to know how to overcome them and understand that the immediate benefits it brings to our industries are spectacular.

AI must be aligned with business objectives and not a stand-alone implementation. This requires leaders to integrate AI into their strategic vision and begin setting an example by integrating it into our companies so we can confidently advise others to do the same.

We must work on cultural change management, data quality and privacy, team training, model transparency, and technological integration. Overcoming these challenges requires a strategic approach, ongoing training, ethics, and clear communication to fully leverage AI's potential to improve business processes and efficiently acquire leads, or the specific impact that any other area within organizations needs to have.

In the next article, I'll discuss how we can leverage these insights and share some key tips for integrating AI into sales and business operations.

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