Generative AI is transforming business productivity, but choosing the right platform— including Microsoft Copilot, OpenAI ChatGPT, or Google Gemini—depends on your existing tech stack and specific use cases. Copilot integrates best with Microsoft 365, ChatGPT is a versatile generalist with strong API support, and Gemini excels in data-driven tasks within Google Workspace. SMEs should assess alignment with business goals, ease of integration, usability, cost, and security. The best strategy often involves piloting multiple tools, ensuring employee training, and implementing governance to unlock AI’s full potential while managing risks.
Here John Shackleton, head of European Systems and Support Services at Sharp Europe, looks at the key differences between the main competing generative AI formats, along with the key features a business should consider when integrating AI into its workflows.
Integrating generative AI into business operations isn't just a trend; it's becoming a competitive necessity. Like any significant technological investment, however, selecting the right AI platform requires careful consideration and strategic planning. Businesses must identify and prioritise use cases, develop comprehensive integration workflows, and implement robust safety measures to protect their operations and data.
The market leaders Microsoft Copilot, OpenAI's ChatGPT, and Google Gemini each bring unique strengths to the table. This guide breaks down what each platform offers to help business leaders make the most informed choices for their organisation.
Here's a summary of the content on this article:
1. An Overview: Microsoft Copilot, OpenAI ChatGPT, Google Gemini
2. Microsoft Copilot: Best for Microsoft-centric workflows
3. OpenAI ChatGPT: Best for versatile, general-purpose AI
4. Google Gemini: Best for Data-Driven and Search-Heavy Workflows
5. Considerations when choosing the right AI platform
6. How SMEs can choose the right AI platform
7. Sharp Microsoft Copilot Consulting Services
8. Conclusion: There is no ‘one size fits all’ to AI for SMEs
An Overview of Generative AI platforms:Microsoft Copilot, OpenAI ChatGPT, Google Gemini
Microsoft Copilot: Best for Microsoft-centric workflows
Microsoft Copilot represents the tech giant's vision for AI-enhanced productivity. It’s designed to work seamlessly with the Microsoft 365 ecosystem. For organisations that rely heavily on Word, Excel, PowerPoint, Teams, and other Microsoft tools, Copilot feels like a natural extension. This makes it especially attractive to businesses already invested in Microsoft products. From drafting emails and generating reports to summarising meetings and organising data, Copilot enhances productivity across administrative, analytical, and content-creation tasks.
Microsoft's strategic advantage comes from this workplace integration, positioning Copilot as less of a standalone AI and more of an intelligent companion throughout the digital workday. Copilot inherits Microsoft’s enterprise-grade security protocols and compliance standards, thereby ensuring business data is protected in line with Microsoft 365 policies.
Why choose Microsoft Copilot:
● Your business is heavily invested in the Microsoft ecosystem
● You need AI assistance directly integrated with Microsoft 365 applications
● You value AI that understands your business's internal context and data
● You need enterprise-grade security and compliance features
OpenAI ChatGPT: Best for versatile, general-purpose AI
OpenAI's ChatGPT pioneered conversational AI that brought large language models into the mainstream. With a conversational interface and the ability to summarise long-form content, generate creative ideas, or write technical documentation, ChatGPT is a strong generalist.
Its tiered approach offers varying capabilities across free and premium versions, with Plus, Team, and Enterprise subscriptions providing access to more powerful models and features. What separates ChatGPT from its competitors is its first-mover advantage and extensive ecosystem. The platform's plugin marketplace enables third-party integrations that extend its functionality, allowing it to perform specialised tasks from data visualisation to internet searches.
Why choose OpenAI ChatGPT:
● You need a versatile, general-purpose AI assistant
● You value cutting-edge language capabilities
● You need strong programming and technical content support
● You want an AI solution that can grow with you through API access
Google Gemini: Best for Data-Driven and Search-Heavy Workflows
Google Gemini, rebranded from its earlier iteration as Bard, combines generative AI with Google's extensive search and data capabilities. It is the least developed of the three compared here but is quickly developing a skillset of its own. Designed for businesses deeply integrated with Google tools, such as Search, Analytics, Ads, and Workspace, Gemini offers seamless connectivity and adds intelligence to workflows powered by Google’s ecosystem.
It works best when handling large datasets and answering complex queries. Whether analysing marketing data, generating insights from spreadsheets, or automating tasks within Google Docs and Sheets, Gemini supports efficient, informed decision-making. It also has an intuitive ‘brainstorm’ mode that can ask questions that can help with wider problem solving within a business.
Why choose Google Gemini:
● Your business uses Google Workspace as its primary productivity suite
● Your business needs support with text, image, and potentially audio
● You value integration with Google's search capabilities
● You want an AI assistant that can handle visual content effectively
Considerations when choosing the right AI platform
When choosing Microsoft Copilot, OpenAI ChatGPT, Google Gemini, the decision will ultimately come down to ecosystem integration, specialised capabilities, and business models. Microsoft Copilot works best within Microsoft's productivity suite, ChatGPT offers the most mature third-party integration options, while Google Gemini capitalises on Google's leadership in search, as well as service integration.
Whichever generative AI tool a business decides to integrate into its workflows, there are potential issues with each. They may generate inaccurate or misleading information, for example. Not only can information be inaccurate, but models can also confidently generate false information. As a result, the use of all AI tools requires careful fact-checking to be the most productive and accurate.
Equally, sensitive business data should not be shared with AI models due to potential data retention and usage by the tools without a proper understanding of whether it is a closed model, or open to wider access.
All Large Language Models (LLMs) are trained on massive datasets and come in two essential different forms: Open and Closed LLMs. Closed LLMs, like GPT-4 or Gemini, are proprietary systems where the underlying model weights, training data, and architectural details remain confidential, with access provided only through controlled APIs or interfaces managed by the developing company.
In contrast, Open LLMs make their model weights publicly available for download, modification, and deployment, often accompanied by detailed documentation about their training process.
This difference has profound implications: closed models typically offer more polished, safety-filtered experiences with guaranteed uptime but limit user control and customisation, while open models provide complete flexibility for fine-tuning, local deployment, and research purposes, though they require more technical expertise to implement effectively. The choice between them often comes down to whether users prioritise convenience and reliability or control and customisation.
How SMEs can choose the right AI platform
Selecting the right AI platform is a strategic decision for any small or medium-sized enterprise. With a growing number of solutions available, it’s essential to evaluate each option by prioritising business needs and expansion plans. Here we take a look at the main areas research should cover:
Business Alignment: Start by identifying the specific goals AI can help the business achieve. This may be in the form of streamlining operations, enhancing customer service, or boosting overall efficiency. Also, ensure the platform aligns with industry and company size. Some AI tools are tailored for small teams and startups, while others are designed for large enterprises with complex infrastructures.
Integration Capabilities: A good AI platform should fit seamlessly into any existing workflows. For example, if the team works extensively within the Microsoft ecosystem, tools like Microsoft Copilot may provide smoother integration. Additionally, check for API access or plugin availability, which enables customisation and ensures the AI can work well alongside your current software stack.
Usability: As with any tool integration with a business, ease of use is vital. This is especially true for teams without deep technical expertise. A user-friendly interface can reduce onboarding time and minimise the need for extensive training. Don’t forget to review the quality of customer support and documentation; having access to helpful resources and a responsive helpdesk can make a big difference.
Cost-Effectiveness: Make sure the platform’s pricing structure aligns with business budgets. Consider all potential costs, including subscription fees, implementation expenses, and any hidden charges. Scalability is equally important – opt for a platform that can grow with a business without leading to disproportionate increases in cost.
Performance and Capabilities: Determine whether the platform can handle the types of tasks needed, such as generating content, analysing data, or acting as a virtual assistant. The platform should also produce reliable, accurate results consistently, especially if you're automating critical business functions.
Ethical and Security Considerations: Trust and compliance are non-negotiable. Ensure the platform follows strong data privacy standards and complies with relevant regulations. For businesses that handle sensitive customer data, this is especially true. It's also wise to choose AI tools that incorporate ethical safeguards to prevent misuse or biased outputs. You can find out more about such things reading our Challenges and risks of AI adoption blog.
Sharp Microsoft Copilot Consulting Services
To effectively utilise AI tools within the business, organisations should look to train employees on the importance of data security and the best ways of working with AI before implementation.
Sharp Microsoft Copilot Consulting Services offer expert consultancy to help teams adopt and onboard Microsoft Copilot in the most secure and efficient way. We make the AI consulting process simple and guide you every step of the way, ensuring you fully realise the value of using Copilot.
If you're looking to securely enhance efficiencies across your organisation, confidently empower your teams with knowledge to excel in their roles, and enable yourself to make informed, data-driven decisions, our Copilot Consulting Services are here to help.
Contact us to get started on your AI tool adoption journey.
Conclusion: There is no ‘one size fits all’ to AI for SMEs
When choosing a generative AI solution for business, the best AI tool ultimately depends on specific business needs, existing technology investments, and use cases. Many businesses find that different AI assistants serve different purposes within their organisation. Microsoft Copilot may excel for internal productivity, while ChatGPT might be preferred for creative content generation, and Gemini could be valuable for research-intensive tasks.
The most strategic approach may be to pilot different tools for specific use cases, measure their impact on productivity and outcomes, and develop a nuanced AI strategy that leverages the strengths of each platform. Remember that regardless of which AI assistant is used, developing clear usage policies, providing adequate training, and establishing governance protocols will be essential to maximising value while managing potential risks.
