Boost Enterprise Productivity with Generative AI and LLMs

Learn how to redesign work in your enterprise organisation using Generative AI and Large Language Models – as discussed in our new GenAI whitepaper. In this latest blog post, we explore how GenAI technologies are transforming enterprise productivity, to deliver positive impacts on the bottom line.

GenAI-powered productivity is making headlines

Here's a compelling case study of how a leading retail finance provider leverages Generative AI to dramatically boost productivity.

Klarna, the “Buy Now, Pay Later” retail finance provider, reports that its new GenAI assistant is making a big productivity impact, now handling two-thirds of customer service chats – equivalent to the work of 700 full-time human employees.

Klarna’s GenAI assistant, integrated with OpenAI’s GPT-4 LLM, has reduced repeat enquiries by 25% and resolves typical tasks in under two minutes, a significant improvement from the 11 minutes taken by human agents. It is available 24/7 and can communicate with customers in over 35 languages.

Klarna says the new system is expected to contribute to a $40 million investment improvement in 2024. The company also announced it has paused hiring of new employees, as a result of its GenAI productivity gains.

This breakthrough in AI-driven customer service means superior experiences for our customers at better prices, more interesting challenges for our employees, and better returns for our investors,” says Klarna co-founder and CEO Sebastian Siemiatkowski.

Exploring the Surge of Generative AI and LLMs within Enterprise Workflows

Indeed, the concept of 'intelligent' digital technology has become mainstream across enterprise sectors. For years now, many companies have been using well-proven machine learning (ML) techniques to automate tasks, analyse data and enhance decision-making. 
However, the scope and impact of ML have been limited by the complexity and expertise involved in training and improving ML algorithms.

That is, until now. Thanks to technological innovations such as pre-training, transformer architecture, cloud scale and orchestration techniques, we have entered the era of Generative AI (GenAI) and Large Language Models (LLMs). 


As discussed in my recent blog post, these are powerful GenAI systems that can create new content, such as text, images, code and video, based on existing data and user inputs. They can also understand and generate natural language, reason intelligently and adapt to different tasks and domains. Organisations can now leverage their proprietary enterprise data with GenAI to deliver customised and powerful business solutions.

GenAI transforms enterprise workflows and productivity

Generative AI and LLMs represent a paradigm shift – creating new enterprise opportunities, unlocking business impact and disrupting the foundations of digital transformation. 

GenAI and LLMs provide unique capabilities that can enable your organisation to streamline, augment and redesign its workflows, processes and digital tools. With capabilities like natural language understanding, reasoning, and adaptability, Generative AI technologies are setting new standards for efficiency, effectiveness, and innovation in various business domains and sectors.

GenAI in action for enterprise productivity

Here are some of the ways that Generative AI and LLMs are transforming enterprise workflows and productivity:

Workflow automation: These solutions use an LLM to automate specific, predefined workflows involving data processing, transformation, interaction and decision-making. Workflow automation can reduce manual labour, operational costs and human errors, and speed up outcomes.


For example, Elsewhen has been exploring how GenAI and LLMs could be used to automate workflows across underwriting, a process that traditionally involves manually assessing various data sources to determine an appropriate premium for an insurance policy. 


With LLM workflow automation, an insurer can feed these inputs into a model, automatically synthesise the information, and output a recommendation to the underwriter.

Conversational interfaces: While conversational interfaces and chatbots have been around for years, they previously had poor language recognition and contextual understanding, making it very frustrating to converse with them. 
New GenAI-powered chatbots and assistants use natural language interfaces that connect an LLM to a knowledge base, such as a database, CMS, HR documentation or financial data, to automate question answering.
Conversational interfaces can improve customer experience, employee productivity and information accessibility by providing fast, accurate and personalised responses to queries.

GenAI co-pilots: These tools use an LLM to augment workflows, increase the efficiency of users and dramatically redesign how they do their jobs. Co-pilots enable collaboration between a human and a GenAI model to achieve a goal or complete a task. The GenAI model provides suggestions, information, or even completes parts of the task based on the user's input. 
This can include drafting emails, writing code, or assisting with problem-solving. 
Co-pilots can enhance user performance, creativity and satisfaction by offering timely and contextually relevant support. 
For example, the GenAI-enabled software coding tool Cursor comes with a built-in co-pilot that sees a developer’s recent changes and can auto-suggest the next edit, or write code based on natural language instructions, leading to significant productivity gains.

Autonomous agents: These advanced solutions use an LLM to execute end-to-end tasks with almost human-like ability. Autonomous agents use a combination of techniques to plan and direct multiple LLM threads towards set goals. 
They can leverage external tools, databases, web content or enterprise proprietary data, to optimise performance – and can react to and align their next action based on the previous output. 
Autonomous agents can tackle intricate challenges independently, without requiring human intervention or supervision. 
For example, an autonomous agent could be used to generate and execute an online marketing campaign, based on the target audience, budget and objectives.

How organisations can accelerate their implementation of GenAI

As you can see, Generative AI and LLMs offer tremendous potential for enterprise organisations to transform their workflows and productivity. However, implementing these technologies is not a trivial task. It requires a clear strategy, a deep understanding of your business challenges and opportunities, a robust technical infrastructure, and a responsible and ethical approach.

At Elsewhen, we specialise in helping organisations harness a cutting-edge approach to design and technology to deliver positive impact. We have extensive experience and expertise in delivering digital transformation for financial services, retail, engineering, healthcare and other sectors. Together, we can define and accelerate your implementation of GenAI, helping you to:

• Identify your opportunities by conducting comprehensive research into the potential of GenAI within your organisation.

• Align your GenAI plans with your strategic objectives, and present it to stakeholders in a business-oriented way.

• Design initial GenAI experiments and evaluate learnings, exploring diverse use cases and testing what GenAI can achieve within your organisation.

• Iterate and expand the scope and scale of your GenAI strategy to provide a detailed service blueprint and solution architecture – and help you implement your GenAI solutions.

If you are interested in learning more about how Generative AI and LLMs can transform your enterprise workflows and productivity, please get in touch with us. 

You can also read our new GenAI whitepaper, in which we outline the emergence of Generative AI and LLMs, highlight GenAI capabilities and product paradigms, and explore potential business impacts and best practices.

Download the whitepaper: Digital Transformation in the Era of Generative AI