Since ChatGPT became available, we have all learnt about the potential of large language models and generative AI in streamlining and enhancing corporate functions. ChatGPT is a leading chatbot, and got a further boost in the market recently when OpenAI introduced personalized chatbots, called GPTs. These are versions of ChatGPT tailored to the users specific tasks, at work, or at home. They mark a step forward in innovating business modernisation. However, ChatGPT is one of a broader set of available solutions. The range includes Microsoft Copilot, Google Duet, Amazon Q, and Anthropic’s Claude 2. Numerous enterprises are currently evaluating these tools to determine the best fit for their needs and exploring their applications.
In this post, I examine the benefits of generative AI, how process intelligence can complement it for data-driven automation, as well as producing a data core for tailored process automation with GPTs.
The Advantages of Generative AI: A Multifaceted Tool
Generative AI chatbots, like ChatGPT, offer diverse applications in automating and augmenting work. The number of their use cases grows as we learn more about their capabilities. Applications include:
- Automating customer interactions and FAQs.
- Enhancing content search, summarization, and translation.
- Streamlining sales and marketing, aiding in content creation and personalized engagements.
- Personalizing education and training initiatives.
- Supporting employees with content creation, report drafting, summarization and translation.
- Analyzing unstructured data for insights.
- Providing decision support through data-driven insights.
Implementing Generative AI in business processes can yield significant savings. For instance, an enterprise used generative AI for pricing calculations, saving nearly 50 hours of manual work weekly compared to a team using traditional methods.
Geography matters in ROI
It is important to note that the benefits depend on factors such as geographical location and staff salary scales as well as the rate of adoption. Taking Microsoft Copilot for Office 365 with a minimum package of 300 licenses as an example, and an optimistic 20% up tick in productivity. In the US this would result in $18.4 per month at 5% adoption by licensed users to $482.7k per month after 12 months at 80% adoption. The same deployment would result in $9.7k and $290.8k in Germany respectively. In India the return would only turn positive with 80% adoption of the technology by the licensed users over 12 months.
Therefore, it is paramount to be clear on who gets a Copilot license, why, and what it would do for them. It is also important to help the member of staff to make the most of the technology and so increase the levels of adoption in order to achieve the best returns.
Making informed decisions and targeting processes and requirements clearly would deliver the best outcomes.
A Data-driven Approach to Deployment of Generative AI
As illustrated in the above example, deciding where to deploy Generative AI requires more than a trial-and-error approach for best returns. KYP.ai’s Productivity 360 platform utilizes process insights to identify optimal application areas for Generative AI. The platform also provides comparative before and after analyses and ongoing monitoring.
It can guide the organisation to deploying the technology where the best efficiency outcomes can be achieved.
By utilizing the insights, process optimisation leaders can become the experts, the sages of operations in their business units, and make decisions with confidence.
A Data Core for Tailored GPTs: A New Era of Process Optimization
KYP.ai’s Productivity 360 platform not only identifies Generative AI opportunities, but it also creates a foundational process data core. This data core can be integrated with new generation chatbot GPTs to develop tailored solutions for process optimization. The process data core allows GPTs to analyse it to make actionable and conversational recommendations, improving decision-making for process optimization and modernization.
First, you get the digital core produced by KYP.ai, allowing you to make the most of your own process information. You can then feed the data core to a GPT and tailor the deployment to make decisions on process enhancements based on geography, roles and processes.
Next you can measure the impact of the deployment by using KYP.ai to continuously monitor operations. You can then make further data-driven decisions on how to refine the GPT deployment to improve the outcomes.
Conclusion: A New Frontier in Work Automation and Augmentation
Generative AI is poised to revolutionize enterprise operations. When combined with process intelligence it enables unprecedented levels of work automation and augmentation.
Don’t miss out on this opportunity to be at the forefront of the generative AI revolution in business.
Contact us today to start your journey towards a smarter, more efficient future.
KYP.ai Communication 
Sarah Burnett 