How will artificial intelligence shape the future of data visualization?

“Reflecting on the rapid advancement of machine learning (ML) and artificial intelligence (AI), it's interesting to see their impact on various sectors, especially data visualization. Recently, I worked on a report that captures the future landscape, informed by insights from around 50 experts working with data products.  

AI has shown much potential to boost productivity and creativity in our work. They are changing how we create diagrams and graphs, making traditional methods almost outdated. Yet, despite these advancements, we still face significant challenges. Data privacy concerns, long response times, and inaccurate outputs are pressing issues we must address to fully harness the potential of AI-driven tools.  

Interestingly, even as we see the rise of text and audio builders, experts believe graphical interfaces will continue to play a crucial role. This hybrid approach to diagram creation seems promising, especially when it comes to detecting AI hallucinations and verifying output accuracy.  

This report provides a clear overview of how AI is reshaping the diagramming market and offers predictions for future trends. By addressing current challenges and anticipating future needs, it aims to equip business owners, consultants, tech experts, and product managers with the knowledge to navigate and leverage AI-driven solutions in data visualization effectively."

Maciej Teska

CEO at Synergy Codes

Highlights from our report

• 77% of respondents claim that the most needed feature among those rated is an AI layout refiner, which improves diagram layout by avoiding cross-links and by grouping elements to provide a better overview and enhance readability.  

• In addition, 80% of developers would most likely integrate an AI layout refiner into their tools.

• 87% of CEOs indicate a Diagram prompt builder as the most valuable feature, which builds diagrams from scratch or develops existing ones using input from prompts.

• 80% of product managers perceive an AI sketch to diagram converter, which converts an image, such as a hand-made drawing, into a fully editable diagram, as the most needed feature.  

• Around 83% of CTOs also claim that an AI sketch to diagram converter is the most useful feature among those rated in the survey.  

• Because of their complexity, building diagrams using traditional techniques such as drag-and-drop will become ineffective. However, people will use them to enhance AI outputs.  

• Data privacy, long response time, and inaccurate outputs are some of the biggest challenges for AI-driven tools.  

• In the upcoming years, graphic interfaces will still be used to create diagrams and will coexist with text and audio builders.  

• Data visualization can play an important role in detecting AI hallucinations.  

• Companies that plan to leverage AI solutions need support in integrating them and in suggesting new features for their tools.  

• Despite the growth of AI, there will always be a need for real relationships, human creativity, imagination, thought processes, and experiences.

‍Report methodology and key metrics

Survey

The survey was launched on March 13 and closed on March 22, 2024, with 48 qualified respondents:  

• CEO/Co-founder (17%).

• CTO/IT Manager (12%).

• CPO/Product Manager/Product Owner/Product Director/Head of Product (21%).

• Developer/Software Engineer/Software Architect (31%).

• Other (19%).  

Respondents were asked to evaluate 10 features based on their descriptions and videos, and to rate how likely they would be to integrate each solution into their product on a scale from 1 to 5 (1 - "Not likely at all", 2 - "Not likely", 3 - "Hard to say", 4 - "Likely", 5 - "Extremely likely").

The responses were then categorized into three groups based on the likelihood of implementation. Group I: "Not likely at all" and "Not likely"; Group II: "Extremely likely" and "Likely"; Group III: "Hard to say".

Expert interviews

In addition to the survey, we conducted interviews with some of the experts who participated in the survey to gain deeper insights into their experiences and perspectives. The interviews were held in May and June 2024.

The insights from these interviews were used to complement the survey data and provide a more comprehensive understanding of the needs and perspectives of professionals working with diagrams and graphs.

Chapter 1. Survey: Emerging trends in AI for diagrams and graphs

This part of the report presents survey results that summarize votes for each feature received from all the respondents and particular professional groups.  

Respondents were asked to evaluate 10 features based on descriptions and videos and rate how likely they would be to integrate each one into their product.  

Here’s what we found.

AI layout refiner  

This AI assistant improves a diagram’s layout by avoiding cross-links and by grouping elements to provide a better overview and enhance readability.

More than 77% of all respondents chose AI layout refiner as the feature they would most likely integrate with their product, making it the best-rated feature of the whole 10.  

This outcome proves that respondents feel that ensuring the readability of diagrams and graphs to be their biggest challenge and where they need support.  

But how do these results break down in the context of specific professional groups? Take a look at the chart below.

The chart shows that over 60% of respondents from each professional group voted for implementing this feature into their tools. This result confirmed the votes from all the respondents.  

However, Software Engineers are the most interested in the AI layout refiner, as 80% of them claim that they would like to use it. This may be because developers, software architects, and engineers are often directly engaged in creating complex diagrams and graph structures.  

Nevertheless, the group of CEOs, Co-founders, and Product Managers displays similar interest, which proves that business-oriented experts also want to use an AI layout refiner.  

AI sketch to diagram converter  

This feature converts an image, such as a hand-made drawing, into a fully editable diagram.  

The AI sketch to diagram converter is the second highest-rated feature, receiving around 71% of votes from all respondents.  

The high score may prove the growing interest in leveraging OCR technology for digitizing text files and images. However, let’s take a look at how particular professional groups rated this feature.

The result shows that the AI sketch to diagram converter received the most votes from CPOs, Product Managers, CTOs, and IT Managers. These groups also have the lowest percentage of votes in favor of not integrating this feature into their products.  

CPOs and Product Managers may see the AI sketch-to-diagram converter as a valuable feature for enhancing their products, and that can increase their market value. Although the OCR technology that this feature leverages is well-known, its potential for digitizing drawing into editable form is still to be discovered.  

Diagram prompt builder  

An AI assistant that helps build diagrams using prompts. It can create them from scratch or develop existing ones with an advanced language model.

The third best-rated feature is the Diagram prompt builder. Around 67% of respondents want to integrate it into their tool.  

Prompt builders are one of the most popular features emerging nowadays, based on the popularity of ChatGPT. Perhaps the familiarity of how prompt builders work or the awareness of the clear benefits that arise from working with them are two reasons why respondents voted for this feature.  

Look at how these results break down in the context of specific professional groups.  

The group most interested in this feature is CEO and Co-founder. Around 88% of them would most likely integrate the Diagram prompt builder into their tool. In addition, no one from this group claimed that they wouldn’t like to use such a feature, and only 12.5% declared that it’s hard to say.  

CEOs and Co-founders might feel that prompt builders are becoming increasingly common add-ons in software, regardless of industry. This might push them to integrate a similar feature into their products so that they do not fall behind their competitors.  

Search assistant  

This AI assistant is equipped with an advanced search tool that visualizes answers to your questions directly on the diagram.  

Search assistant gathered around 56.5% of respondents' votes and is the fourth best-rated feature. However, a significant 27% of voters claim they wouldn't be likely to integrate this feature into their tools.  

As for results from specific professional groups, they break down as follows:  

CEOs and Co-founders (75%), who are business-oriented experts, are the most likely to use this feature. More tech-oriented experts, such as Software Engineers, also show interest in Search assistant (around 67%).  

An interesting dependence emerges in the CTO and IT Managers group. 50% of respondents claim that they wouldn’t be likely to integrate this feature into their tools, while only around 17% would do so. We can only assume that this group’s hesitancy stems from integration, security, or other challenges.  

Anomaly detector  

This feature discovers outliers, anomalies, and errors, to which you can attach a comment for future revisions.  

The feature that closes the top five best-rated features from the survey is the Anomaly detector, which around 55% of voters would like to integrate with their tools. In addition, around 21% of respondents are not decided yet, and 25% wouldn’t use this feature.  

As for results from specific professional groups, they break down as follows:  

Software Engineers (67%) and Product Managers (60%) are the most interested in this feature. Meanwhile, respondents who held executive positions, such as CEOs and CTOs, seem hesitant to integrate the Anomaly detector. 75% of CEOs who participated in the survey claim they would not likely leverage this feature, or it’s hard to say right now. A similar opinion is shared by CTOs, of whom around 67% claimed that they also would not leverage this feature, or it’s difficult to say right now.

The rest of the features  

The second half of the rated features gathered less interest from the respondents, with fewer than 50% of the votes in favor of integrating each feature.  

They include:  

1. AI group finder. An AI assistant that defines new patterns and groups them. You can review them one-by-one or accept all suggestions at once.  

2. AI property prediction. This AI assistant spots missing properties in your diagram or graph. You can review these changes one-by-one or approve them in batches all at once.

3. Diagram seeker. This feature uses your search preferences to locate a corresponding diagram in your database, making it quicker to build a new one.  

4. Diagram and graph copilot. An AI assistant that suggests live graph structures based on your historical data. It can offer additional links as well as nodes and their properties.  

5. Link analyst. This AI assistant predicts new node relationships and suggests their placement. You can review them step-by-step or accept all suggestions at once.  

The chart below presents their performance in the survey.

As you can see, almost 50% of respondents voted in favor of integrating four features into their tools. However, the rate of "Hard to say" and "Not likely/Not likely at all" answers is also significant. This shows that these features do not seem urgent to respondents, and they don't feel a need to leverage them right now.

Chapter 2. Experts’ opinions on the impact of AI on the data visualization market

To dig deeper into the survey results, we asked six experts who actively participated to share their thoughts on some additional questions. We asked them:

1. How can AI features in data visualization tools help end users?  

2. Will AI soon generate graphs more intensively than it does now?  

3. What are the challenges for the development of AI-powered diagramming solutions?  

4. Will text or audio interfaces replace graphical interfaces?  

5. Can data visualization help in detecting AI hallucinations?  

6. Do experts need more than integration with a prompt builder to simplify working with complex diagrams?  

7. Do companies need support for integrating AI features?  

8. Will AI eventually replace some kinds of jobs?

How can AI features in data visualization tools help end users?

Frank Joublin, Principal Scientist at Honda Research Institute

Principal Scientist since 2001 at the Honda Research Institute Europe GmbH, where he is involved in research on AI-based multi-agent systems. Frank’s research interests include developmental robotics and semantic acquisition.  

“I think that AI can help boost creativity and design diagrams faster. In addition, if you’re not skilled in drawing, instead of drawing a diagram or graph by yourself, you can use speech to draw and create one.  

AI can also generate and interpret diagrams or graphs, read them, and understand what they represent, including relationships between nodes. It can help users determine what to modify on the diagram and what nodes or objects to add or remove.  

For example, you can select a part of a graph and ask an AI assistant if it’s the best way to represent an idea. Or maybe there is a better option for that?  

So, AI can help you generate more ideas, accelerate your work with creating diagrams or graphs, and eventually help you interpret them or make them more accurate.”

Daniel Balaceanu, Chief Product Officer at DRUID AI

CPO and a co-founder of DRUID AI with over 25 years of experience in building enterprise solutions. With a PhD in Business Computer Studies, Daniel infuses AI, machine learning (ML), natural language understanding (NLU) and natural language processing (NLP) into DRUID - a conversational business applications platform.

“One of the biggest benefits of using AI for end users is boosting productivity. Everything is related to productivity.  

The complexity of diagrams increases, so you can’t build them in the traditional way by using drag and drop and designing everything.  

Looking at the complexity of my projects that involve building graphs that handle conversations with hundreds of steps, it’s not realistic anymore to develop them using old methods.  

Another thing is that when I design a diagram, I would like to get help from an AI model to tell me if I should design it this way or that way or if I have the following sinks in my diagram to take care of.  

I think it’s beneficial to have an AI model that understands my data, whether they are conversation transcripts, sales orders, HR documents, etc.”

Will AI soon generate graphs more intensively than it does now?

Frank Joublin, Principal Scientist at Honda Research Institute

“For sure, AI in the future will generate graphs more intensively than now. This is a trend that will stay with us.

Let’s take an example. For every domain where you need a kind of map visualization, it’s impossible to describe it using words. By seeing a map, you can show something on it, point to it, interact with it, and highlight some aspects. This is something you can’t do using only words. You can’t describe complex structures only with words.

So, I think we’ll have more and more AI solutions that generate graphs because they are a great means to represent complex data.”  

What are the challenges for the development of AI-powered diagramming solutions?

Anubhav Srivastava, CEO and Co-founder at VocaTales

Anubhav is the Co-Founder and CEO of VocaTales, a startup headquartered in Chicago, USA. VocaTales is a collaboration platform that simplifies the process of creative, impactful content for digital writers and creators.

"I think the most significant obstacles are security, data privacy, people's acceptance, and the ethical dimension of AI.  

The security aspect is nothing new—there are still companies that would use on-premise solutions rather than leverage cloud services offered by established companies such as AWS, Google or Microsoft. AI is no different, early adopters will move in, others will join later. Some won't show up at all.  

Adding to that AI, some people might have ethical doubts because they're unsure where the data comes from and if it includes people's personal details or intellectual property.  

So, as a consequence, they still determine if they should use AI solutions trained on such data of unknown origin. In addition, they are afraid of what will happen to their data.  

For me, it's a significant challenge because I build my product as a social platform and potentially offer it to 200 million creators or writers. It means I must address these ethical concerns.  

Users should have the right to choose whether to opt in or opt out of AI features in products they use. If they don't want it, AI models should not consider their data."

Daniel Balaceanu, Chief Product Officer at DRUID AI

"Data security concerns all my projects, and I must take care of it, especially in all new technology I use. Each technology should be embeddable in my product. It means that I must host it and manage the entire data flow.  

Most of our customers leverage technology from the cloud. We also manage cloud services. However, then we audit everything and guarantee that we are the only ones that hold our customers' data.  

And if we use third-party services like OpenAI for Microsoft subscriptions, we must sign data privacy contracts. And we work only with already accepted providers in the enterprise sector like Microsoft or Google.  

As for other challenges, the performance of AI models is not a big obstacle. From my experience they usually respond in 1-2 seconds.  

In complex implementations, you can onboard the respective hardware or ask Microsoft or any other provider for special subscriptions.  

The market is moving in that direction to have faster response time and I see it especially in the US market. I have talked with several banks, and they're starting to apply hardware just for multiple experiments with generative AI.  

So large businesses are getting prepared for broader use of AI solutions."

Francois Vanderseypen, CEO at Orbifold Consulting

Graph Scientist, Technical Consultant and CEO at Orbifold Consulting. Francois helps startups navigate in the world of technologies and high-tech, trying to comprehend frameworks and platforms to estimate their range and scope in function of consultancy and customizations.

"If a company wants to have AI on-premises, it's the point where things become complicated.  

My observation is that if you want to train a model, you need huge amounts of data, infrastructure, and experts like data engineers and DevOps specialists. But that's a bit of a problem. For me, it's a job of its own.”  

Frank Joublin, Principal Scientist at Honda Research Institute

"The first constraint that comes to mind is data protection. One day, we might have to develop LLM to protect our sensitive data.

The second is the large language models' response time. If it’s too long, you will get bored and stop using them.

And, of course, users must also cope with AI's well-known problem - the hallucinations that cause you can't be sure that the AI outcome reflects the truth.

Another problem is that when LLMs are updated, they may behave differently. As a result, you might have to redefine your prompts because the models don't understand them the same way as their previous version.”

Peter Theunis, Co-founder of Erisna

Co-Founder of Erisna, an intuitive data governance platform that allows organizations to better understand all their data assets, improve their data quality and ensure data compliance.  

"When it comes to “AI-powered solutions” there are some challenges. The typical ones are resources – not only the budget but also the lack of experienced specialists. More specifically, finding those suppliers that are trustworthy and substantially better than in-house developers. The problem is that it’s tough to separate trustworthy vendors' because wide-scale AI usage is relatively new, experts are still figuring it out and meanwhile there’s a lot of boasting about skills.    

Another interesting observation is the push for integrating AI into software solutions.  And whilst AI is the future, at its current stage, it shouldn’t be the most pressing development on every product roadmap. The most pressing items should be related to solving customer problems and with that comes getting your basics right. So, a potential bigger obstacle I’m noticing in the market is companies being forced to integrate AI into their tools, and by doing so, they might not be focusing on what they should do.    

As an example, having a Chat GPT prompt builder is very cool to have on your platform, we all agree with that. But it’s extra functionality, once you get the essence of your solution right."

Simon Sarris, Software Developer at Northwoods Software Corporation

Simon builds GoJS, a JavaScript and TypeScript library for interactive diagrams in HTML Canvas and SVG. It involves API design, documentation, and developer-to-developer support.

"Surely, the obstacle is a lack of data to train models. Large language models need extensive data to be helpful. It's a fundamental limitation. I think the big problem with our model is that we don't have enough training data and good, simple examples of beautiful diagrams to train it and make something worthwhile.  

So that's why we feel that we should wait and see. Maybe in a few years, there will be models that can do a lot more with a lot less. But right now, they need a lot of data to be useful.  

There's also the privacy concern, at least for some companies. If you offer a tool, you can scare some people who are worried that if they start using anything from your company, you'll start using their data to train your models.  

If you offer a tool that does anything automatic, you must be sensitive to the customer and make sure they know you're not trying to take any of their data at the same time."

Will text or audio interfaces replace graphical interfaces?

Frank Joublin, Principal Scientist at Honda Research Institute

“I don’t think that graphical interfaces will disappear like that because you can’t explain the same thing using plain text or speech instead of a visual interface – it would take too much time.  

A lot of people think visually and represent concepts using boxes and links. Written and spoken language is suitable for many aspects, but not for all of them. There are domains where graphical representation is needed because language cannot describe thoughts and concepts. I think the graphical representation will stay, and the audio interfaces will coexist.”

Daniel Balaceanu, Chief Product Officer at DRUID AI

"It's a tricky question. It sounds like we no longer need graphical interfaces, such as traditional tables, charts, and graphs. And that all of us will stop using any other kind of interaction except text and audio.  

It doesn't work like that.  

The models themselves evolve. At first, Chat GPT provided just text input. Now, I can upload images and get output based on them.  

So, in my opinion, the models will evolve to offer a multimodal experience, engaging users not only through text or audio but also with other forms, including diagrams.  

I believe I could soon form a prompt like that: I want to create a conversation graph that allows customers to be onboard for a credit application. My credit application should capture the following parameters. It's integrated with SAP with three back-end APIs. Can you draft the diagram for me, please?  

I think general domains will be involved in developing AI solutions in this direction, specialized models will appear, and existing business applications will start having such functionalities."

Anubhav Srivastava, CEO and Co-founder at VocaTales

“I think that graphical interfaces make so much sense and will develop in the future.  

Take a look at the younger generations, such as Generation Z and Alpha. Those kids love video games that are based on graphical interfaces. There’s no kid that doesn’t spend time watching Minecraft videos.  

Looking at how they think, they process visual elements much faster than written text.  

It doesn’t mean that text will disappear because you need text to create all the visuals. You must write all the details that you need first.  

But graphical interfaces will continue being important because they help people think and act faster.”

Peter Theunis, Co-founder of Erisna  

"In my world, despite many advancements, people lean towards visuals and graphical representations to form or showcase conclusions. Those visuals then get supported with a narrative. The narrative is very important, however at this point, it seems that visualizing helps people understand and form conclusions. Typically, for any graphical representation you’d have numerous data points, which could easily be shown in tabular, text or audio format, yet as a society we seem to be sticking to graphical interfaces for important items    

Let's take data lineage or data mapping. The idea behind it is how can I showcase a data flow in an appealing way so that the person looking at it can understand it and make quicker decisions. There’s no reason we couldn’t explain this through text or audio yet as end-consumers we prefer a visual interface.  

I don't think it will change anytime soon."

Simon Sarris, Software Developer at Northwoods Software Corporation

"I think it's not true. Firms make a lot of virtual assistants, but users also really don't like using them.  

Perhaps we don't make enough visualizations, or maybe they're not good enough, but they're still the king.  

Text is superior in a lot of cases. But I don't think visualizations are going to go away anytime soon.  

And I think most people are tired of chatbots. Even though companies aren't tired of making them."

Francois Vanderseypen, CEO at Orbifold Consulting

"Graphical interfaces, like BI dashboards, will remain. In any case, people will always like bar charts. Text will not replace charts, and a paragraph can't replace mind maps. So, text and graph interfaces are complementary. However, I suspect that Chat GPT will be able to create a dashboard at some point."  

Can data visualization help in detecting AI hallucinations?

Anubhav Srivastava, CEO and Co-founder at VocaTales

"Even visual data can lie. It still can hallucinate. But because people's attention span is shorter and shorter, we must see things faster.  

How can you spot errors in a document that is pure text? We must visualize it first to make it easier to consume and analyze. That's exactly what we are doing on VocaTales through storyboarding."

Simon Sarris, Software Developer at Northwoods Software Corporation

"I always have this example in the back of my mind with machine learning. One of the first very successful machine learning applications ever was PayPal in the early 2000s.

They built this very early machine learning system to detect fraud. But one characteristic of payments is that you're very fuzzy about what is fraud and what isn't.

So, a human must review the results. If you're crunching hundreds or thousands of transactions and can get a view at the end, you should have a chance to order it or make it more readable. So that person can look at the results and say: those seven transactions look bad.

So, visualization is essential for a person who has to review all of those outcomes."

Do experts need more than integration with prompt builder to simplify working with complex diagrams?

Daniel Balaceanu, Chief Product Officer at DRUID AI

“Having good LLMs and knowledge on how to use them effectively for diagram creation is, in my opinion, the winning part.  

Prompt builders can theoretically accelerate building diagrams. However, in practice, when I apply them in production, I sometimes realize I don’t have much control. I write a text describing how the model should behave, but then it doesn’t behave how I expected. It’s difficult to troubleshoot and understand what happened. For instance, why did the conversation move on that path, or what are the paths?  

So, we need tools to handle that.  

Prompt builders can also create complexity that is difficult for a user to handle. Suppose a prompt builder generates a diagram with 80 steps. In that case, you must take over this outcome and adjust it after it finishes. So, instead of simplifying, the model creates complexity that the user must handle now.”

Do companies need support for integrating AI features?

Francois Vanderseypen, CEO at Orbifold Consulting

"There's a huge interest in AI, but businesses need guidance in leveraging it.  

You can't keep up with everything that is happening—the framework, AI, language models, the difference between some types of diagrams, whether you choose Meta or Microsoft.  

So business owners need guidance in the first place to make sense of all of the things that are going on. Requesting augmented generation is usually the second thing.  

For instance, people have PDFs, knowledge graphs, or PostgreSQL databases and want to know what it takes to use natural language to talk to your database. That's the typical case.  

People or companies do that partly to attract new employees and show that their firms are up to date with tech news.  

So, my role is often to offer something like a guide in the first place because I know how you can go somewhere and what it takes. Where you can search for this type of model or tools that you can utilize with projects for your customers."

Will AI replace some kind of jobs eventually?

Francois Vanderseypen, CEO at Orbifold Consulting

"There are some areas that I would happily hand over to AI. However, helping clients create custom applications and understanding their business processes, data pool, and user interactions are all tasks for people.  

What I do is more than coding. I can't imagine an AI that sits in a meeting for long hours and listens to political clashes between different departments within a big organization. And that's also what I do. Let's remember that AI is a technology and not a human being. It can't replace humans in dealing with all the complexity of corporate life.  

So, I'm not afraid that AI will replace my business consultancy role soon. And I have a similar opinion as for custom development services.  

Another thing is that I don't want AI to handle me with the creative part of my work because I enjoy it.  

Business is about dealing with people, talking to them, and understanding their ideas or visions. There are rational and irrational aspects, social dynamics, communication, trust, and other vital elements.  

Business owners talk to each other because they believe it results in some wisdom and is more meaningful than asking Chat GPT.  

Sitting at a table and having dinner sometimes is just as important for business as developing JavaScript.  

So, business owners should invest in good relationships and kindness."

Daniel Balaceanu, Chief Product Officer at DRUID AI
“Currently, companies are using SAP and mobile applications. But should I say those companies are run by SAP or Power BI reporting tools only because they use them daily for making decisions?  

I would say no.  

Those tools are used by humans and humans drive the business.  

Artificial intelligence is a catchy and provoking name, but that’s it. It’s not that robots and AI will replace humans. The humans who won’t use AI will lose their jobs.”

Frank Joublin, Principal Scientist at Honda Research Institute

"It has already happened in some areas and is a risk no one should underestimate. Nevertheless, it is the responsibility of all of us to try to develop solutions that have a positive impact on society.  

For instance, it can be used in domains without humans involved because of unrealistic costs. I think of personal teachers for every child, personal aids for elderly people, or personal moderators of your social media interactions. The idea is to use AI to complement and collaborate instead of replacing.  

So, it can replace some jobs. However, AI will initially help many specialists do their work more efficiently."

Antonello Ceravola, Principal Scientist at Honda Research Institute

At Honda's Research Institute, he researches and develops large-scale software systems for Honda prototypes like such as cars, robots, and intelligent systems. His Antonello’s work is increasingly centered on artificial intelligence, particularly in robotics, advanced driver-assistance systems (ADAS) and multi-agent systems (MAS).  

"One thing I remember from one of the conferences I took part in was a speaker from Microsoft who said that it will take time for AI to reach performance of human workers in many domains, however jobs like data scientists are among the few jobs that could likely be performed by AI at a great extent.

Of course, we must consider that it has been said by a Microsoft employee who works closely with OpenAI. So, he might have wanted to convince the audience that this is the future.  

So, now AI helps people rather than replaces them, and we can hope it will stay like this for a long time. But it's only a hope if we consider the fast AI evolution we are experiencing and the inertia such ethical concerns can be regulated by our societal structures"

Anubhav Srivastava, CEO and Co-founder at VocaTales

"The dust has to settle. I think there is a crazy amount of uproar about AI everywhere.  

Just this week, I interviewed around 100 sixteen- to twenty-two-year-olds, asking them about their point of view on AI and where they think it stands. Almost everyone said that AI is a great addition to enhancing human creativity. But, in the end, the real revolution and changes must come from the human brain.  

As the dust settles slowly and steadily, AI will become an integral part of everything that we do.  

It already has become. However, when it comes to the kind of work involving human creativity, imagination, thought process, experimentation, and experiences, its results will still trump what some AI-generated work produces. All the more when humans collaborate to create and transform the future for the better."

Conclusion

Integrating AI into data visualization tools opens new avenues for enhancing users' creativity and productivity. With AI, they can create, interpret, and optimize diagrams quicker and more efficiently, especially for complex projects.  

However, challenges like data privacy, response times, inaccuracies, and ethical concerns need to be addressed. While AI can automate many tasks, it can't match the creative and strategic thinking that humans bring. That's why AI should be seen as a complement, not a replacement.  

Graphical interfaces remain essential for building and using graphs or diagrams, even as text and audio interfaces become more common. A mix of different types of interfaces seems to be the key to making AI practical and user-friendly.  

In the future, AI will likely play a larger role in generating and managing graphs or diagrams. However, human involvement will always be necessary to ensure accuracy and relevance. The most effective AI solutions will blend technology with human insights, balancing automation with the unique value only people can provide.