Most organizations require Information Technology (IT) assistance to implement GPTs (Generative Pre-trained Transformers), and even more so to develop AI Agent teams.The current moment presents a unique opportunity to implement artificial intelligence for competitive advantage and will seldom be this favorable again.
Empower Your organization with AI Assistants
AI Assistants, powered by advanced models like Generative Pre-trained Transformers (GPTs), represent a straightforward and highly accessible initial application for integrating artificial intelligence within your organization’s operations.
- Contrary to the notion that they require minimal development, deploying AI assistants effectively does involve a degree of customization and integration to ensure they meet specific business needs. While GPT models come pre-trained on extensive datasets and are capable of handling a wide array of tasks right out of the box, optimizing these systems to align with particular business objectives and workflows typically necessitates additional training on specialized data and integrating these systems with existing technological frameworks.
- Utilizing Microsoft’s Power Platform can be a highly effective way to deploy GPT-powered AI Assistants. The Power Platform provides robust tools and infrastructure that help in seamlessly integrating these AI capabilities into your existing systems. This platform not only simplifies the process of deploying AI solutions but also offers powerful analytics and business intelligence capabilities to enhance decision-making and operational efficiency.
As your organization considers introducing AI into operations, it is important to understand that while the base technology is sophisticated, achieving the best outcomes will require thoughtful implementation, ongoing management, and possibly iterative development to tailor the AI’s functionality to unique organizational needs.
Creating an AI assistant (GPT) for each business role
Creating an AI assistant (GPT) for each role can begin with a natural language setup and by granting access to the data necessary for fulfilling the role. Additionally, it should adhere to organizational rules that enforce branding standards.
How Your organization can implement GPTs
Define Roles and Responsibilities
First, clearly define the different roles (e.g. sales, support, marketing) and their respective responsibilities within the organization. This will help tailor the AI assistant’s knowledge and capabilities.
Curate Role-Specific Knowledge
- Gather all relevant data for each role – product/service details, process documentation, FAQs, best practices, etc.
- Ensure brand guidelines, tone of voice, and messaging rules are well-documented.
- Combine the role-specific knowledge with brand guidelines to create comprehensive training data for each custom GPT model.
Train Custom GPT Models
- Use a platform like CustomGPT.ai to create and train separate GPT models for each staff role using the curated data.
- During training, emphasize adherence to brand guidelines by including examples of on-brand and off-brand responses.
- Optionally, use techniques like Reinforcement Learning to further reinforce brand compliance during model fine-tuning.
Deploy and Integrate Assistants
- Once trained, deploy the custom GPT models as conversational AI assistants accessible to employees in their respective roles.
- Integrate the assistants into existing workflows, knowledge bases, and collaboration tools for seamless adoption.
- Implement feedback loops to continuously improve the assistants based on staff inputs and brand guideline updates.
Key points about using custom GPTs (Generative Pre-trained Transformers) to connect to third-party APIs and services:
Custom GPTs Can Integrate with APIs
Custom GPTs created through OpenAI’s GPT Builder can be granted access to integrate with external APIs and services through “Custom Actions”. This allows the GPT to retrieve data or perform actions outside of the ChatGPT interface.
Connecting to APIs via Custom Actions
To connect a custom GPT to an API like Google Cloud Storage:
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- In the GPT Builder, go to the “Add Actions” page to define a new Custom Action.
- Provide a schema/specification describing how the GPT’s output should be processed and sent to the API.
- This schema would reference your own backend code that handles the API integration logic.
OpenAI’s Assistants API
Using OpenAI’s Assistants API: OpenAI’s Assistants API can also be used to build custom AI assistants that integrate with external services and APIs directly within applications. This requires more development work compared to the GPT Builder approach.
Calling Assistants from Custom GPTs
While it is possible to call an OpenAI Assistant via a Custom Action within a GPT, the recommended approach is to build the Assistant integration directly into applications using the Assistants API. GPTs are designed more for user-facing customization within ChatGPT.
Summary
The key benefit of GPTs is their ability to provide specialized, personalized assistance and insights by training them on specific data, processes, and requirements to leverage the power of AI while maintaining brand consistency and domain expertise.
Customizing GPTs for specific roles represents an optimal use case for small businesses aiming to incorporate the productivity benefits of artificial intelligence into their daily workflows. Additionally, Microsoft’s Power Platform supports solutions that extend its well-known products like SharePoint and Office 365, thereby minimizing the risks typically associated with adopting new technologies.
Michael Stuart
