Imagine a world where your workforce spends less time on repetitive tasks and more on high-impact activities that truly drive value. Well, we’re not imagining anymore — Generative AI is making this a reality across industries. From how generative AI improves productivity in financial services to enhancing customer experiences in retail, the rise of these Generative AI agents is reshaping the way employees work. But while this technology boosts efficiency and decision-making, what’s the real-world impact on employees? Are we witnessing the dawn of a productivity revolution or just a fleeting tech trend?
Let’s dive into six case studies that showcase generative AI applications, illustrating how generative AI improves employee experience and overall performance. These stories reveal not only improved workflows but also how AI empowers teams, driving transformative outcomes in productivity and efficiency.
1. Morgan Stanley: Streamlining financial advisor workflows with GenAI
Morgan Stanley aimed to improve the efficiency of its Financial Advisors (FAs) during client interactions, seeking a solution to streamline the handling and analysis of over 1 million annual conference calls.
The firm launched the AI @ Morgan Stanley Debrief tool which records, transcribes, and summarises key points from calls, integrates with Salesforce, and drafts follow-up emails for advisors. By standardising data collection, Morgan Stanley gains deep insights into client interactions.
The AI solution enhanced efficiency, saving advisors time and enabling consistent data analysis. This provides real-time insights, improves client service, and helps align advisor communication with strategic goals.
"AI @ Morgan Stanley Debrief has revolutionised the way I work. It's saving me about half an hour per meeting just by handling all the notetaking. This has really freed up my time to concentrate on making decisions during client meetings. It's been a total game-changer. "
Don Whitehead, Financial Advisor, Morgan Stanley
In fact, customer support agents using Generative AI to assist with conversations saw a productivity increase of nearly 14%, with the greatest impact on less experienced workers, who improved by 35%. Meanwhile, highly skilled workers experienced little to no negative impact, maintaining their performance levels effectively. (NBER, 2024)
2. Victoria’s Secret: Enhancing in-store experiences with generative AI agents
Victoria’s Secret aimed to boost the efficiency and productivity of its in-store associates, ensuring they could provide accurate product recommendations and improve customer experiences while streamlining internal operations and training.
By integrating generative AI agents, the company enabled associates to quickly access information on product availability, inventory, and sizing tips. They also explored Google Cloud’s generative AI technologies to automate associate onboarding, training, and job description creation, enhancing HR support.
The result is a more intuitive shopping experience and an optimised supply chain, ensuring products reach customers at the right time and place.
3. Goldman Sachs: Solving internal workflow challenges with generative AI
Goldman Sachs sought to address internal workflow challenges, including a shortage of technical talent and the time-consuming nature of documentation processes. The aim was to improve productivity while maintaining the accuracy of business operations.
The firm developed generative AI applications, including a natural language coding tool and a documentation automation platform. The coding tool allows employees to generate code efficiently, while the automation platform streamlines the process of filling out complex sector-standard documents using generative AI insights.
These tools have improved employee productivity by reducing coding time and ensuring documentation processes remain efficient and accurate. This internal focus on GenAI-driven automation helps the firm navigate tech challenges while preparing for broader future applications.
Research on the impact of generative AI on employee productivity highlights software development as the area experiencing the most significant gains. Developers using Generative AI for coding saw a remarkable 126% increase in project output per week.
4. WellSky: Elevating healthcare operations with AI insights
WellSky needed to modernise its healthcare solutions to help providers manage a growing volume of patient data, reduce administrative burdens, and deliver better care. Manual tasks, such as data entry and analysis during care transitions, consumed time that could be better spent directly with patients.
Through a strategic partnership with Google Cloud, WellSky integrated Vertex AI into its platform. This integration automates tasks like the Outcome and Assessment Information Set (OASIS) assessment for Medicare home healthcare. AI-driven insights provide healthcare providers with instant access to contextually relevant patient histories, trends, and anomalies, improving decision-making during care transitions.
WellSky’s generative AI tools significantly increased operational efficiency, allowing clinicians to focus more on direct patient interactions. Automating assessments and providing instant access to critical patient data reduced time spent on routine data entry. This improvement enhanced the quality of care and enabled providers to respond quickly to patient needs. The AI tools also created a consistent framework for data analysis, aligning with WellSky’s commitment to responsible, secure AI implementation, ultimately driving better patient outcomes and service delivery.
5. Uber: Enhancing technical support with GenAI copilots
Uber faced inefficiencies in managing internal support, with on-call engineers fielding around 45,000 queries monthly across various Slack channels. The need for quick and accurate information retrieval strained resources, diverting engineers from more complex problem-solving tasks.
Uber implemented "Genie," a generative AI copilot using Retrieval-Augmented Generation (RAG) models. Genie integrates with Slack to quickly access internal documentation, such as wikis and past support records. It answers technical queries autonomously, providing engineers with instant, contextually accurate information without needing direct human assistance.
Genie has significantly enhanced efficiency, handling over 70,000 support interactions across 154 channels. It has saved approximately 13,000 engineering hours by resolving common inquiries, allowing engineers to focus on critical projects. The AI’s ability to maintain a 48.9% helpfulness rate has also improved the speed and quality of internal support. Uber’s investment in Genie demonstrates how generative AI can streamline workflows, empowering teams to tackle high-priority issues while minimising time spent on repetitive support tasks.
6. McDonald’s: Automating recruitment with GenAI assistants
McDonald's faced challenges in managing high-volume hiring across its global operations, where restaurant managers often had to balance recruitment with daily operations. This resulted in a time-consuming hiring process and delayed response times to job applicants.
McDonald's implemented "McHire," a recruitment platform powered by Paradox’s AI assistant, Olivia. Olivia manages initial candidate screening, schedules interviews, and answers recruitment questions through a text-based application process. This allows applicants to apply quickly through a simple text interaction, while Olivia handles the administrative workload.
McHire reduced time-to-hire by 65%, enabling managers to focus more on customer service. With Olivia handling routine recruitment tasks, McDonald’s improved the candidate experience, offering a faster, seamless hiring process. The AI solution streamlined recruitment, allowing McDonald's to efficiently meet staffing needs across corporate and franchise locations.
Generative AI isn't just for big players—It's for you too
At first glance, the generative AI case studies above might make you think that implementing this technology is only for industry giants with deep pockets. But that’s not the whole picture. The brands leading the way are showcasing generative AI use cases that any business, large or small, can learn from. Their successes serve as a blueprint, demonstrating how AI can be adapted to fit your unique needs.
With the right partner, you can easily develop custom solutions or find the right tools to streamline operations, enhance employee experience, and reduce costs. Building an AI-enabled culture doesn’t have to be complicated, but it does require the right strategy. Our team at Calls9 is here to offer a free consultation to help you navigate these decisions. We’ll listen to your challenges and provide tailored advice on how generative AI improves productivity in your specific context.
As MIT Sloan insightfully puts it:
"Generative AI can boost worker productivity, but organisations must first establish a culture of accountability, reward peer training, and encourage role reconfiguration."
Getting Started with End-to-End AI Transformation
Partner with Calls9, a leading Generative AI agency, through our AI Fast Lane programme, designed to identify where AI will give you a strategic advantage and help you rapidly build AI solutions in your organisation. As an AI specialist, we are here to facilitate the development of your AI strategy and solutions within your organisation, guiding you every step of the way:
- Audit your existing AI capabilities
- Create your Generative AI strategy
- Identify Generative AI use cases
- Build and deploy Generative AI solutions
- Testing and continuous improvement
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*The cover image of this article is generated by AI
