Choosing the Best AI for Biotechnology Organizations: Microsoft Copilot vs. ChatGPT
The use of AI in biotechnology is revolutionizing how organizations conduct research, manage data, and enhance productivity.
Two prominent AI platforms, ChatGPT and Microsoft Copilot, have emerged as leaders in the market. Both offer advantages, but which is the best AI for biotechnology?
Given the sensitive nature of the data you likely hold, selecting the wrong AI platform can cause serious security and compliance concerns. In this article, we’ll share the pros and cons of these two platforms, as well as highlight their features, integration capabilities, and security concerns to help you make an informed decision.
ChatGPT: The Pioneer of AI for Biotechnology
ChatGPT was one of the first platforms to popularize AI, using an open-source large language model (LLM) that many other AI tools have since adopted. Known for its web-driven "ask a question" chatbot interface, ChatGPT excels in scenarios where users need quick answers and insights. Its flexibility allows companies to create customized GPTs that fit specific workflows, making it a powerful AI for biotechnology companies focused on research.
ChatGPT excels at creating customized AI solutions that can analyze large datasets, generate scientific literature summaries, and automate repetitive tasks, allowing researchers to focus on complex problem-solving. Its flexibility makes it particularly valuable for companies with strong R&D departments, as it can be tailored to specific scientific workflows. For instance, Moderna’s use of ChatGPT (watch a video summary here) showcases how biotech companies can leverage AI for tasks like generating insights from data and automating repetitive processes, thereby accelerating research timelines.
However, this level of customization often requires a good understanding of AI, coding, and LLMs, which can be complex for non-technical business users. Additionally, ChatGPT’s lack of native integration with commonly used productivity platforms like Microsoft Office can pose additional challenges and expenses, requiring extra development work to fully integrate the AI into daily operations.
Microsoft Copilot: Seamless Integration with a Common Platform
Microsoft Copilot takes the opposite approach by embedding AI directly into Microsoft 365 applications, such as Outlook, Word, Excel, and PowerPoint. By integrating AI into tools that users are already familiar with, Copilot offers a more accessible way to integrate AI for biotechnology organizations—especially small and medium-sized organizations with limited IT staff. This integration delivers instant value, enhancing productivity across teams without the need for extensive technical expertise.
Copilot utilizes a version of ChatGPT’s LLM but with enhanced security measures to protect against vulnerabilities, making it a safer choice for organizations concerned about data breaches. Although Copilot may lag slightly behind ChatGPT in terms of the latest features due to additional security vetting, its seamless integration with Microsoft 365 applications ensures that AI tools are readily available to enhance your day-to-day work.
Copilot also offers detailed usage reporting and license management, allowing companies to efficiently allocate resources. Microsoft’s ongoing development of Microsoft Copilot Studio, which allows users to modify existing Copilots or create new ones, makes it an increasingly competitive AI for biotechnology applications.
Understanding Key Integration Capabilities
Integration with existing tools is a key factor when choosing an AI platform. Currently, there are no direct integrations between ChatGPT and Microsoft 365 applications, although developers have created third-party tools to facilitate some connections. However, third-party integrations often require additional development work, which may not be feasible for smaller biotech companies lacking the necessary technical resources.
Microsoft Copilot’s integration capabilities are more streamlined. It works natively within the Microsoft ecosystem, allowing users to leverage AI tools without the need for extensive setup or customization. For companies that already use Microsoft products, Copilot fits naturally into existing workflows, enhancing productivity with minimal disruption.
Additionally, Microsoft has been exploring integration with other platforms, such as Slack, which could further expand Copilot’s utility in biotech environments. While not yet a fully out-of-the-box experience, these developments indicate Microsoft’s commitment to broadening Copilot’s reach and usability across different business environments.
Security Concerns in AI for Biotechnology
Last but certainly not least, security is a top priority when adopting AI for biotechnology organizations. From proprietary research to sensitive clinical trial data, your organization likely handles multiple different types of sensitive, proprietary, and regulatory-protected or compliance-governed data and information. Here are the top two security concerns:
Data Loss Prevention (DLP). If intellectual property is entered into an AI platform, it can be used to train AI models (giving away your confidential concepts and data to other users) or leaked if the platform is breached. This can have significant consequences and expose proprietary and sensitive data. For example, Samsung experienced a major data breach when an employee used ChatGPT’s public version to improve code, exposing meeting notes and sensitive source code online. Then you have the risk of “shadow AI.” Just like shadow IT, employees and contractors may be using AI platforms that are not approved and unknown to your IT team and not considered in your security plan.
Data security and privacy. One of the big benefits of AI for biotechnology is that it can increase productivity. It can quickly index and search through large volumes of data, emails, and documents, helping you find things faster. It can also index and search through data to summarize information quickly. However, if someone mistakenly puts sensitive information in an unsecured file location, you can increase your risk for a data or privacy breach. For example, if the AI tool is indexing this data and a user accesses an HR spreadsheet (due to a simple access misconfiguration), they could ask the AI about their boss's salary or even request a list of everyone’s bonuses from the previous year. Yikes.
Both products offer ways to mitigate some of these security concerns. ChatGPT, being a newer platform that operates somewhat independently, doesn't have as many built-in tools in this area. In contrast, Microsoft has access to its extensive Defender for Cloud portfolio, Purview, and data governance tools within Microsoft 365. These include DLP (Data Loss Prevention) policies, which are available at various levels, some free and some for an additional cost.
Before we share our choice for the best AI for biotechnology organizations, we want to be clear that platform selection is only part of the process. No matter which AI solution you choose, it’s critical that you update your internal policies and procedures to account for the addition of AI into your cybersecurity and incident response plans. Here are a few of our top tips:
Ensure you have proper network segmentation and Identity and Access Management (IAM) tools and check these regularly.
Define and communicate acceptable use policies that include AI use guidelines to your entire team (including contractors).
Implement strong third-party risk management policies and review your partners’ AI use and policies if they handle any sensitive data.
Have regular configuration reviews and penetration testing for your on-premises, cloud, and web applications.
It can take a lot of time and research to select, implement, and update your security plans for AI. Remember, you don’t have to go it alone. You can also contact our expert team for guidance and support. Now, (drumroll, please) for the choice you’ve all been waiting for: what is the best AI for biotechnology organizations?
Which AI is Right for Your Organization?
Honestly, it depends on the size of your organization and your specific needs.
ChatGPT is ideal for research-driven biotech companies needing a highly customizable AI platform. Its adaptability allows for tailored AI models that can enhance research efficiency and support scientific innovation. However, its lack of native integrations with common business tools and complex setup requirements make it more suited to larger, tech-savvy teams with the necessary resources for integration and customization.
Microsoft Copilot is the better choice for broader organizational use, particularly for companies that rely on Microsoft 365 applications. Its seamless integration, robust security features, and user-friendly interface make it an accessible AI for biotechnology companies looking to enhance productivity without extensive customization or development work. It’s likely the better choice for smaller organizations and those with limited IT and programming staff.
Both platforms offer unique advantages, and you should consider which AI aligns best with your company’s goals, security concerns, and operational needs. By carefully evaluating each option, biotechnology companies can harness the power of AI to drive innovation, streamline operations, and protect their valuable data.
Please contact us if you need help selecting or implementing an AI solution. Our expert team specializes exclusively in IT consulting and solutions for biotech and life sciences organizations.