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As Artificial Intelligence (AI) continues to revolutionize the way we work, we’re all trying to figure out how it can boost our efficiency and productivity. To gain a competitive edge, we need to be AI-savvy. That means using AI tools, taking courses in AI, and attending conferences that help us network and upskill. But before we let the pendulum swing too far, let’s remember that over-reliance on AI — particularly for work that requires empathy and human connection — can backfire.
Keeping real human connections is especially important for life sciences companies that are growing quickly and facing big changes. A connected company culture can be a driver of success, but it demands the right mix of AI help combined with real person-to-person communication.
Here are five mistakes to avoid when using AI in internal communications:
1. Using AI too much for personal communication
When scaling quickly or managing large teams, it’s tempting to automate every message. Over-automating can turn meaningful conversations into robotic exchanges, making employees feel undervalued.
Use AI for routine tasks like scheduling meetings or sending reminders. But let humans handle personal touchpoints such as onboarding, conflict resolution, and one-on-one check-ins. These interactions require empathy, understanding, and a personal touch that AI cannot replicate.
2. Letting AI make people decisions alone
AI should assist, not replace, human judgment in critical employee decisions. AI can process data quickly to spot trends and patterns. But decisions about people need human insight, especially in life sciences, where specialized talent is responsible for innovation.
While AI can help screen resumes, key choices about teams, roles, and company direction need human judgment. This will ensure decisions align with company culture and values while considering the complex human factors AI might miss.
3. Forgetting to check AI for bias
AI systems can pick up and spread hidden biases and create problems for company culture and team trust. Regularly audit and adjust AI algorithms to ensure fairness and avoid discriminatory practices. For instance, implement diverse data sets and continuous monitoring to identify and correct biases. You can also encourage transparency by allowing employees to review AI decisions to catch potential biases early.
4. Not protecting employee privacy with AI
Life sciences companies handle sensitive data daily. Employee data is sensitive and should never be compromised. Ensure robust data protection measures are in place to maintain trust and comply with privacy regulations, avoiding potential breaches and legal issues. Be transparent about data usage and give employees control over their information. Finally, be sure to update your privacy policies regularly and ensure all AI tools comply with these standards.
5. Skipping training for AI tools
AI tools are only as effective as the people using them. Invest in comprehensive training to help your team utilize AI responsibly and to its full potential, fostering ethical and effective use. Provide continuous learning opportunities and resources to keep employees updated on the latest AI developments and best practices. Encouraging a culture of curiosity and innovation will help team members feel comfortable exploring (and questioning!) AI usage.
Potential without pitfalls
Balancing AI capabilities with human connection is key to strong performance for life sciences companies. The goal isn’t just to work faster — it’s to build stronger, more efficient teams that bring life-changing solutions to the people who need them most.
AI helps, but connection matters.
Let’s get it right.
