How to Use ChatGPT in Your Digital Transformation

From data analysis to knowledge management and more, there are many ways AI chatbots can boost your digital strategy.

With all the buzz, press and enthusiasm surrounding ChatGPT, many engineers are exploring how ChatGPT and similar AI chatbots could enhance digital transformation.

Digital transformation is about using technology to transform how businesses operate and deliver customer value. It’s not just about implementing new techno gadgets. It requires a fundamental shift in culture and mindset to achieve success.

How can ChatGPT help? From data analysis to knowledge management to customer service and more, there’s a long list of ways AI chatbots can boost your digital transformation.

Deepen data analysis

AI chatbots can analyze large volumes of data from diverse sources quickly and accurately. This capability is a valuable digital transformation tool for engineers as they confront the need to query, process and interpret large amounts of structured and unstructured data that exceeds what Excel can process and manage.

AI chatbots overcome the limitations of current data analysis tools, including:

1. Poor response times for large queries.
2. Support only simple text string matching for unstructured data.
3. Complexity in describing queries for structured data.
4. Difficulty accessing data stored on various platforms.
5. Difficulty integrating data due to incompatible key formats and values.

AI chatbots can deepen data analysis by searching relevant information to identify patterns and insights by:

1. Responding to more sophisticated queries.
2. Handling complex data integration more easily.
3. Analyzing vast amounts of unstructured data such as reports, literature and web pages.
4. Analyzing unstructured data.
5. Summarizing text.

Manage knowledge

Engineers recognize the value of knowledge management to more rigorously apply the experience from one project to the next. They also understand the impediments, including:

1. Staff turnover.
2. Gaps in the documentation of previous projects.
3. Changing technology.
4. The cost of operating a knowledge management system.
5. Evolving customer and regulatory requirements.

Some organizations have introduced digital transformation to knowledge management by:

1. Advancing digital transformation in their work to capture the requisite digital data.
2. Operating centers of excellence for various professional groups.

AI chatbots can advance knowledge management by:

1. Making internal data easily accessible and searchable.
2. Providing excellent references to external sources for most topics.
3. Generating new literature on most topics, including combinations of hypotheses and theories that could guide future research.

ChatGPT has triggered a debate about the future of knowledge management. Some believe that AI chatbots will finally cause knowledge management to be taken more seriously and be adopted more widely. Others believe AI chatbots will eliminate the need for formal knowledge management approaches and principles because AI chatbots will make so much knowledge readily accessible.

Write content, reports and software

Writing reports, presentations, social media content, and software has been a hand-crafted creative process forever. Similarly, engineers performed design work manually using large sheets of drafting paper.

A rapid digital transformation of these tasks occurred for engineers and many others with the introduction of:

1. Word processors and text editors for reports.
2. CAD/CAM software for designs.
3. Sophisticated editors for graphics, photos, audio and video.
4. Integrated development environments (IDE) for software.

AI chatbots are now taking this digital creative work to a new level by generating social media content, reports, designs, software, graphics and video based on summary text input of what is wanted.

While AI chatbot products still require tuning and correction by professionals, AI chatbots have significantly reduced the associated effort. Two early examples are:

1. Software development: A GitHub research project reports that using the GitHub copilot produced an approximately 50 percent effort reduction and an improvement in developer satisfaction.
2. Photography: Using the text-to-graphic feature of some AI chatbots can reduce photographer effort from hours to minutes by avoiding travel time.

Improve diagnostics

AI chatbots can quickly and accurately analyze large volumes of diagnostics data from Industrial Internet of Things (IIoT) sensors. This capability is a valuable digital transformation application for engineers who analyze machinery performance data with a view to:

1. Improving performance.
2. Predicting failures and reducing unscheduled outages.
3. Diagnosing root causes more quickly and accurately.

The following issues limit the current diagnostics process:

1. The complexity of modelling software required.
2. Data volume and data source maximums.
3. Insufficient forecasting and data visualization functionality.

AI chatbots can improve diagnostics by identifying the following:

1. Patterns and relationships that analytics software misses.
2. Targets for intervention earlier and more quickly.
3. Optimizing schedules for planned maintenance outages.

Improve customer service

AI chatbots can understand and process natural language (NLP) input, called prompts, to communicate with engineers conversationally. This capability can digitally transform call centers that many organizations operate.

AI chatbots can be the basis for vastly more capable chatbots or virtual assistants. By more capable, I mean generative question answering that is more specific to your organization’s domain and the customer’s question.

We’ve all encountered frustrations with the current chatbots and call centers. Chatbot shortcomings include simplistic answers and lengthy inconclusive dialogues. Call center issues include navigating complex interactive voice response (IVR) menus, reading long answers to frequently asked questions (FAQ) questions or waiting on hold at length to speak to a representative.

AI chatbots can improve customer service by:

1. Increasing customer satisfaction by providing contextually more targeted and correct answers.
2. Reducing the elapsed time to resolve customer questions.
3. Reducing the number of calls handled by more expensive call center staff interactions.
4. Filtering emails, SMS, and texts, sorting spam from real consumer messages. For legitimate communication, the AI chatbot prepares recommended responses for call center staff to finalize.

Improve forecasting

It’s impossible to predict the future. However, digital transformation can help engineers avoid guessing and narrow the confidence interval of various likely future scenarios.

AI chatbots can overcome the limitations of current forecasting software. These limitations include the following:

1. Simplistic models leading to low-confidence forecasts.
2. Restrictions on the amount of data that can be ingested.
3. Data quality lapses casting doubt on the usefulness of forecasts.

AI chatbots can improve forecasting by:

1. Using more sophisticated and likely more realistic models.
2. Considering more data sources and more extended time series.
3. Including data sources, often external to the organization, the forecaster did not consider.

Reduce mind-numbing administrative overload

A surprising number of organizations continue to handle many routine administrative transactions manually. Engineers are invariably sucked into error resolution. Some organizations have implemented robotic process automation (RPA) as a step toward digital transformation to:

1. Improve the work experience of their employees.
2. Accelerate processing to increase efficiency.
3. Increase processing accuracy.
4. Reduce the number of exception situations and errors.

Unfortunately, current transactions processing software is constrained by the following:

1. Customer and vendor errors.
2. Limits on the sophistication of automated processing rules.
3. Errors interpreting scanned documents.

AI chatbots can improve transaction processing by:

1. Handling complex processing rules.
2. Reducing the error rate.
3. Increasing throughput.

The capabilities of AI chatbots in NLP, knowledge management, data analysis, diagnostics, and automation make them a valuable asset for businesses looking to enhance their digital transformation efforts.