Make ChatGPT and other AI tools work for your business

AI For Business

Artificial intelligence (AI) has long been predicted to be a trend this year, and businesses around the world are using this new technology in a variety of ways to make their businesses more efficient. ChatGPT’s entry into the mainstream technology arena puts AI in an even brighter spotlight, with many people and companies looking to adopt this popular tool and other professional AI programs. But what are the viable ways to apply proven professional AI tools to your business or try out ChatGPT as an expert?

Alex Pryor, Head of Digital Innovation at EOH, Neil van Wyngaard, Solutions Architect at iOCO Digital, a company proud of EOH, and Nicole Adriaans, Business Executive for Data and Analytics at iOCO, shared some insights and actionable provide a good example.

Alex Pryor: ChatGPT continues to gain traction as it is the first mass adoption of AI technology driven by a natural language processing (NLP) engine. The platform has the fastest acceptance by 100 million users compared to other new AI technologies. ChatGPT brings AI to individuals across society, but until now, capitalizing on machine learning technology required corporate investment.

ChatGPT is very useful, but it is trained not only on reviewed sources such as Wikipedia and scientific articles, but also on the Internet, so you should check all the information it provides. However, integrating your application program interface with ChatGPT can be very useful. For example, use NLP engines to train on very specific data sets such as the Governance Risk and Compliance (GRC) data set.

Since ChatGPT went public, Open AI has launched GPT4. GPT4 is described as a powerful and popular multimodal technology. Many tech giants and startups, including Google, are also investing heavily in AI tools. This reinforces the view that the next version of ChatGPT or Open AI will be able to do more, faster and more accurately.

ChatGPT business application

At this point, you can apply ChatGPT to your workplace to improve productivity. For example, a marketer writing an article can use it to brainstorm ideas on a topic and quickly gather information for interesting articles. You can even design your prompts so that the tool offers its own way of generating content and suggests stylistics and formats.

Businesses can use ChatGPT along with automation to make repetitive casework smarter and more productive. While Microsoft is building AI into Teams to power things like meeting note taking, you can add AI to your chatbots and train them on the right data sets to make them smarter.

The interesting thing about this type of generative AI is that AI algorithms can be leveraged to create new, plausible content using existing content such as text, audio files, and images. This allows computers to abstract basic patterns related to inputs and use them to generate similar content.

Companies considering using ChatGPT and new technologies should understand their strengths and weaknesses. The best way to use ChatGPT is to pick one business use case and try it out. But right now it’s not a good idea to put mission-critical stuff in there. It must be deployed where manual, repetitive tasks occur in the business, and inserted into creative spaces to support the work, but it cannot take over the process. As a result, some tasks may complete faster than before.

ChatGPT brought the possibilities of AI to the public sphere and captured the imagination of many. This allows you to perform manual, repetitive business-related tasks much faster, saving costs and improving efficiency. However, ChatGPT is just one technology in a vast pool of available AI resources, and specialized tasks and industries require the use of specialized AI models and programs.

Neal Van Wingard:

Efficient execution of repetitive tasks

Specialist AI can be applied in the business world where people perform repetitive tasks with well-defined rules. A good example of how expert AI is being used to benefit local financial institutions is the ‘document understanding solution’. EOH was developed for banks and mortgage lenders. This AI tool quickly and efficiently compares the personal and income information loan applicants provide to financial institutions with data from various verification documents. Highlight discrepancies between the two sets of information, make necessary corrections, and identify possible fraud.

AI automation tools make the processing and verification of applicant information highly efficient. Evaluate a single application in seconds, but it is possible to process the application manually.

It involves a team of 40 people processing multiple applications over several days. The obvious advantage of this tool is that it allows an organization to significantly increase his daily trading volume.

Also read: ChatGPT Won’t Eliminate My Job, But It May Eliminate My Therapist’s Job

Companies in retail, finance, manufacturing, and other sectors are increasingly adopting AI automation tools from procure-to-pay. This is his EOH solution that manages the process of receiving and processing vendor invoices from start to finish. You received an email with an invoice attached, opened your accounting system, and built a bot to process the invoice. The system is very popular and is showing increasing interest to companies in various sectors.

Companies looking to experiment with AI or use it to solve business problems should first check whether there are existing AI tools in the market that can meet their needs. In greenfield scenarios, where companies want to build their own AI, selling it to other organizations can create value for their investment.

Generic AI and Specialist AI

General-purpose AI tools like ChatGPT for different data sets are unlikely to add value in specialized business areas. This is because, to be effective, an AI application (using a specific data set) must be performed in the context of a specific area, task, or issue. Simply put, if you have a specific purpose, you should build your AI tools to make sense of that purpose.

The reason there are so many different AI companies is that each one focuses on a niche area and has its own machine learning models and data sets that are not shared with other companies. As such, there is no ChatGPT or AI tool that can answer all questions.

Nicole Adrians:

Predecessor of ChatGPT and AI

Advanced predictive analytics, the predecessor of AI tools, have been applied by enterprises for decades. Traditionally, advanced predictive analytics has been a natural evolution of the descriptive analytics companies have had in the form of business intelligence and dashboards. For example, the banking sector has been running predictive analytics models for a long time, but they are running them on statistical analytics systems. The difference now is that machine learning technology speeds up the process significantly.

Applications in banking and retail sector

Almost every sector can benefit from NLP technology. Retailers typically use specialized AI tools to customize their offerings to their customers. With AI, you can gather more information about individual customers, so you can offer them the most compelling products and deals. AI helps the retail sector retain customers and build customer loyalty.

A common application of expert AI in the retail sector is call center optimization. The NLP engine can read the emotion of the caller’s voice and smartly return calls to her members of senior staff when dealing with angry customers. As a result, the risk of problems is reduced or reduced.

The banking sector is deploying specialized AI to help prevent and detect fraud. Network analytics, which identifies connections between customers based on internal and external data, helps banks identify who is connected to fraudsters, enabling financial institutions to exercise more financial control. Become. Banks are also applying data science in smart ways in the area of ​​agricultural lending.

Some industries in South Africa have excelled in adopting AI. The challenge is the pervasiveness of AI in the community and public sector. State enterprises and departments should use it. We need to pull the country up until all sectors trust and buy in.

Alex Pryor A seasoned technical executive. She is Head of Digital Innovation at her EOH, one of her largest IT companies in Africa, focused on identifying and implementing new technologies that drive business growth and value. . Alex is a regular speaker at industry conferences to share her expertise on topics such as emerging technologies, blockchain, innovation and women leaders.

Neal Van Wingard is an experienced solutions architect at iOCO Digital, an EOH proud company. He is a seasoned engineering professional with a proven track record in the information technology and services industry. Neil is passionate about teaching and helping others grow professionally.

Nicole Adrians is a data and analytics business executive at iOCO, an EOH company. Since 2009, she has successfully designed and implemented data and analytics solutions across her chain of business Her Value, from Omni Her Channel to Omni Her Digital Her initiative.

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