Wednesday, May 31, 2023

How ChatGPT is Transforming Enterprise Search with Natural Language Processing

By Swapnil Mishra - March 30, 2023 6 Mins Read

How ChatGPT is Transforming Enterprise Search with Natural Language Processing

Organizations must decide whether ChatGPT can be successfully integrated into their IT environment to develop cutting-edge enterprise apps.

The release of OpenAI’s ChatGPT has generated much excitement over the last few months. Due to its abilities, it has received much attention and provoked debates on the future of artificial intelligence.

With industry giants like Microsoft, Google, and Meta entering the fray, businesses can expect an exciting but potentially turbulent journey ahead. It will be fascinating to see what technological advancements and developments in artificial intelligence take place soon now that ChatGPT has raised the bar for computing capabilities.

Using large language models (LLMs), including a specific generative LLM that powers the system, is the foundation of ChatGPT’s capabilities. LLMs have been around for a while, but their innovative potential and scope are expanding significantly.

It is truly unique how quickly this field develops, with discoveries being made constantly, spurring even more development in language models. Many have viewed its introduction as a challenge to Google, the undisputed leader in web search, and its hegemony. Microsoft has already announced a sizable investment in OpenAI, the company behind ChatGPT, presumably seeing this as an opportunity to up the ante against Google.

The situation is made much more intriguing by reports that Bing, Microsoft’s web search engine, will soon utilize ChatGPT. However, ChatGPT’s effect on Google’s hegemony is not the main topic of discussion.

Organizations must decide whether ChatGPT can be successfully integrated into their IT environment to develop cutting-edge enterprise apps in light of the buzz surrounding it.

Firms need to assess if it would be a game-changer and significantly enhance organizational practices, social media/customer engagement strategy, e-commerce objectives, and customer service.

Also Read: Top Transforming Enterprise Data Strategies

Behind the scenes of AI

Additionally, a lot going on “behind the scenes” has confused me. As a result, some people have mischaracterized ChatGPT as a Google competitor or believed that generative AI would eventually replace search.

It’s crucial first to make a distinction between search and generative AI. Information retrieval, or surfacing existing information, is the goal of the search. Applications like ChatGPT and generative AI use what the LLM has been trained on to create something new.

ChatGPT, however, does not retrieve content or information as a search does; instead, it creates an imperfect reflection of the information it already knows. It isn’t much more than a random collection of words that were put together using probabilities.

LLMs can enhance a search experience even though they won’t replace search. The real benefit of using generative LLMs in search is convenience: the ability to condense the results into a clear, understandable format. Combining generative LLMs with the search will create new opportunities.

Better Search Results Using Language Models

LLM application to search was previously both expensive and time-consuming. However, this started to change last year as trailblazing businesses integrated LLMs into enterprise searches, representing a significant advancement in search technology that will provide quicker, more accurate, and forgiving results. But this journey is just getting started.

Organizations can anticipate a significant increase in the power and capability of these models in the coming year as newer, better LLMs become available and existing LLMs are refined to complete particular tasks. Businesses will be able to locate specific answers within the document instead of just finding them. IT teams will retrieve information based on meaning rather than exact keywords.

LLMs will produce better results by surfacing the most pertinent content, delivering more targeted results, and communicating in natural language. Additionally, generative LLMs have great potential for condensing search results into digestible summaries that are simple to find.

Using Search to Prevent Knowledge Loss

Organizational knowledge loss is a severe but frequently disregarded problem that businesses today face. Vital information is often left stranded on “information islands” due to high employee turnover rates, whether caused by voluntary attrition, layoffs, M&A restructuring, or downsizing.

The transition to remote and hybrid work, significant shifts in employee and customer perceptions, and increased unstructured data and digital content contributed to the difficulty. Knowledge management has been put under great stress as a result.

A recent survey of 1,000 IT managers at large companies found that 67% were concerned about the knowledge and expertise that departing employees take with them. IDC estimates that failing to share knowledge costs Fortune 500 companies $31.5 billion annually, highlighting the high cost of knowledge loss and ineffective knowledge sharing. This number is especially concerning in light of the current unstable economical environment.

A Fortune 500 company with 4,000 employees could save about $2 million monthly in lost productivity by improving information search and retrieval tools. A crucial tool for preventing information islands and enabling organizations to easily find, surface, and share knowledge and corporate expertise is intelligent enterprise search.

In the digital workplace, easy access to knowledge and expertise is crucial. The right enterprise search platform can link disparate information silos and connect workers to knowledge and expertise to promote discovery, innovation, and productivity.

A search resolves application fragmentation and digital friction

Today’s workers are buried under their tools. A recent Forrester study, Crisis of a Fractured Organization, found that organizations use 367 different software tools on average, which leads to data silos and messes up teamwork.

Employees, therefore, divert 25% of their time from doing their jobs to finding information. Not only does this affect employee productivity, but it also affects revenue and client outcomes. Through constant app switching and switching from one tool to another to complete tasks, this “app splintering” worsens information silos and creates digital friction.

A recent Gartner survey found that 44% of users made the wrong choice because they were unaware of information that could have been helpful, and 43% of users said they missed important information because it got buried under too many apps.

Employee experiences are unified by intelligent enterprise search, enabling seamless and accurate access to all corporate knowledge from a single interface. This dramatically reduces app switching and employee annoyance while streamlining productivity and collaboration for an already worn-out workforce.

Also Read: Top Data Analytics Trends That Will Effect Businesses in 2023

What does ChatGPT’s commercial future entail?

ChatGPT has the potential to change how businesses operate. ChatGPT may alter how time and resources are allocated because of its capacity to automate repetitive tasks, provide real-time data analysis, support multiple languages, and enhance data accuracy.

While implementing ChatGPT may present some difficulties, such as tech support issues and privacy worries, the advantages of using AI for the company may outweigh the drawbacks. How quickly and successfully businesses adopt and integrate the technology into their operations will probably determine ChatGPT’s future impact.

However, ChatGPT and other AI programs like it will likely significantly impact how businesses operate. ChatGPT is a solution that companies, big and small, should consider to achieve their long-term objectives, whether they want to increase customer satisfaction, spur innovation, or stay ahead of the competition.

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Swapnil Mishra

Swapnil Mishra is a Business News Reporter with over six years of experience in journalism and mass communication. With an impressive track record in the industry, Swapnil has worked with different media outlets and has developed technical expertise in drafting content strategies, executive leadership, business strategy, industry insights, best practices, and thought leadership. Swapnil is a journalism graduate who has a keen eye for editorial detail and a strong sense of language skills. She brings her extensive knowledge of the industry to every article she writes, ensuring that her readers receive the most up-to-date and informative news possible. Swapnil's writing style is clear, concise, and engaging, making her articles accessible to readers of all levels of expertise. Her technical expertise, coupled with her eye for detail, ensures that she produces high-quality content that meets the needs of her readers. She calls herself a plant mom and wants to have her own jungle someday.

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