on the second anniversary of chatgpt
AI's Impact and the Next Two Years
To coincide with the two-year anniversary of ChatGPT, we asked some of our favorite AI practitioners and experts to reflect on the impact this technology has had over the past two years, to offer their best advice for leaders looking to take the next step, and to offer their opinions about what’s coming in the next two years.
Read their responses here. Check out, download, and share the infographics.
Click on the infographic to view and download a full-size version.
What’s the biggest impact ChatGPT has made on business over the past two years?
We asked AI experts to share their take on how ChatGPT has altered the business landscape since it arrived in November 2022 release. They highlighted how it has democratized AI access and is boosting productivity for organizations, executives, and individual contributors alike. While it offers opportunities and challenges by shifting views on human capital—raising questions about task automation and even role replacement—many professionals face a dilemma about embracing AI tools or risking their career relevance. Experts note a surge in innovation and startups fueled by AI’s hype, yet some caution that the true transformative impact may still lie ahead, and there have already been missteps and flawed investments among both startups and established companies.
David Armano
CX Strategist & Enterprise AI Executive
I think the immediate impact to date from ChatGPT is primarily 2 areas. First, the advent of ChatGPT has essentially become the driving force for how Google has been redeploying ever since the LLM went public. In addition to fast-tracking Gemini, Google is racing to reinvent its role in the future as more people shift to LLM based interactions over traditional search. Without ChatGPT, Google would have largely stayed the course it was on prior to the LLM revolution.
And second, ChatGPT has made a huge impact in the small business world including startups where enterprise-grade data security is less of an issue. The API combined with the CustomGPT ecosystem is allowing for startups to launch with MVPs in record time.
Courtney Baker
Chief Marketing Officer, Knownwell
The actual impact to date has come via the execution layer of business. Across a large swath of business, there have been productivity gains on an individual level. In addition, businesses have had to think about humanity in a way that is unlike what we’ve had in modern business—what makes us different than machines, what are the things we want to keep, how do we utilize AI to elevate humanity rather than destroy it.
Shashi Bellamkonda
Principal Research Director, Info-Tech Research Group
ChatGPT revolutionized the AI landscape by making AI accessible to anyone with internet access via a simple browser interface, significantly boosting awareness of OpenAI. This move led to heightened user expectations and posed substantial risks to established tech leaders. Prior to ChatGPT, AI was primarily accessible through data scientists and tech professionals. Established companies had been harnessing AI’s capabilities correctly through stages like Analytical AI, Predictive AI, and eventually, Generative AI. However, many businesses prematurely attempted to leap directly into Generative AI without success. Successful companies, on the other hand, took a more measured approach by analyzing their current issues and integrating AI into existing systems or adopting specialized AI solutions. Meanwhile, several rivals of OpenAI and ChatGPT are emerging, gaining traction, and could potentially dominate the enterprise and business AI sectors.
David Berkowitz
Founder, AI Marketers Guild
ChatGPT has empowered a new era of creativity. We’re no more creative than we were two years ago, but now we have more tools to bring ideas to life, from creating mind-blowing visuals to having conversations with our data.
Paul Chaney
Publisher, AI Marketing Ethics Digest
Reflecting on the past two years, ChatGPT’s most notable influence on business may be democratizing access to powerful artificial intelligence. ChatGPT has opened creative, operational, and strategic opportunities across sectors by offering readily available, user-friendly AI tools. These tools enable even small businesses and individuals to employ artificial intelligence without a professional tech team. However, this accessibility comes with a price—the need to use these tools responsibly and ethically—a discourse that badly needs to occur in 2025.
Gam Dias
Product Strategist, Hubbl Technologies
Author, The Data Mindset Playbook
First of all, it’s made me quite lazy… because I immediately asked ChatGPT for an answer. and by God it was a dull response. So, here’s what I think… not only has it STARTED to make us all lazier, it has created an unbelievable amount of hype and with that comes revenue for ‘consultants’ who have decided that this is a great way to generate money by selling snake oil. Organizations are FOMO’ing at the mouth to start building GenAI … GenAI what? That’s the point, just building Gen AI period.
If you rip off the front of the virtual building, you see a lot of individuals using the free accounts to make their jobs easier – just getting ChatGPT to write initial drafts or copywrite from seed ideas. More sophisticated uses are where people that don’t code are now able to generate code and deploy it, whether its automation for their Google Sheets or MS Excel or to write whole applications that they can deploy on the web. In short it has removed a barrier to doing things by substituting technical instruction for just replacing the human. Nothing that we’ve not done before as a species… but this is so powerful that it might leave us in danger of becoming more stupid. Will we be living out the movie Idiocracy within a generation?
Right now, we are at maximum hype… or according to Gartner, we’ve tipped over. But the last 2 years has been a lot of hype – tech media frenzy, lots of startup overvaluation, lots of strategic consulting expenditures. Is there anything to show for it? Experience, mistakes, prototypes, learning, excitement.
Neil Katz
Founder/COO, EyeLevel.AI
In a weird way it hasn’t had much impact on the business world yet. But people probably forget how long the path was from the birth of the web in ’92 to major disruption other than a stock market rush and crash. Google was formed in 98 and Facebook in 2004. Netflix started in 97 and didn’t start streaming until 10 years later. Apple, the biggest winner of them all, almost went belly up in the 90s.
Basically, the FANG that we consider the kings of the Internet age either didn’t exist or were on death row in the first few years after Marc Andreessen made the Mosaic browser and the modern web was born. Tech revolutions, like war, tend to be hurry up and wait.
Geoff Livingston
Chief Strategy Officer, CognitivePath
ChatGPT was the catalyst to turn the long-simmering AI wave into a full boil that enveloped the business world. While there was a lot of what if type of speculation about potential applications that were not realized (yet), ChatGPT provided concrete validation that AI can generate useful text in a variety of ways. Further, the trainable GPT algorithm demonstrated that generative AI can be applied to a variety of outcomes and purposes. Still in the end, within the context of an all-powerful AI, ChatGPT underwhelmed most professionals when applied to complex tasks.
Stephanie Pereira
Chief Operating Officer, Astral
The biggest impact has undoubtedly been in how we think about people resourcing. Even if adoption has only really picked up over the past 6-8 months, and true operationalization is only getting started, the jobs sector is haunted by the specter of ‘AI is coming for my job.’
Dr. Rebekka Reinhard
Founder & Editorial Director, human
The most profound impact has been on the accessibility of knowledge and the democratization of creativity. ChatGPT has enabled companies to harness the power of language and data in ways that were previously limited to specialized teams or external experts. But it has also raised fundamental questions about the relationship between human and machine intelligence in the workplace – challenging organizations to rethink and redefine the role of human ingenuity, intellect, and judgment.
Greg Verdino
Chief Operating Officer, CognitivePath
ChatGPT tipped AI into the mainstream, making it accessible to companies of all sizes, accelerating productivity, and opening new avenues for engagement. But it’s not an unqualified win. When used as just a shortcut to efficiency, we risk trading genuine human insight for convenience. Customer experiences can feel more transactional than relational. And ethical issues abound. ChatGPT’s real value lies in amplifying human expertise and experience, not recycling it, replacing it, and reducing it to some ‘raw average.’ The question now is, how do we ensure widespread use of a technology like generative AI elevates our work without sacrificing what makes it uniquely ours?
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Now that we’re past the peak of the hype cycle, what’s your number one recommendation for businesses looking to incorporate generative AI?
Two years after the launch of ChatGPT, a realistic view generative AI is finally emerging. We asked 10 experts for their top advice for executives implementing generative AI in their organizations. Our experts highlighted several key themes: start with clear goals, define specific use cases, upskill your teams, emphasize ethics, and think more in terms of augmentation than replacement. They also emphasized the importance of AI readiness, change management, and accepting that failure is part of any business transformation.
David Armano
CX Strategist & Enterprise AI Executive
Two years after the launch of ChatGPT, a realistic view generative AI is finally emerging. We asked 10 experts for their top advice for executives implementing generative AI in their organizations. Our experts highlighted several key themes: start with clear goals, define specific use cases, upskill your teams, emphasize ethics, and think more in terms of augmentation than replacement. They also emphasized the importance of AI readiness, change management, and accepting that failure is part of any business transformation.
Courtney Baker
Chief Marketing Officer, Knownwell
Understand how AI will continue to move up the levels of business into operations and strategy. Although the technology has moved incredibly fast in the past two years, we are still at the very beginning. Having awareness of where we are now and a framework to think of future transformation will be incredibly helpful.
Shashi Bellamkonda
Principal Research Director, Info-Tech Research Group
The most effective applications of generative AI are tailored to specific use cases, with leading examples including enhancing customer experience, boosting worker productivity, and automating operations. By employing more specialized AI models instead of large language models (LLMs), generative AI can operate more swiftly, require less computational power, and deliver more precise outcomes.
David Berkowitz
Founder, AI Marketers Guild
Embrace failure. By some measures, the failure rate for AI projects is at least twice as high when implementing other kinds of tech. A large part of that is because this field is so new for most businesses, and the adoption curve scaled so quickly. It’s a great time to fail fast, learn, and keep innovating.
Paul Chaney
Publisher, AI Marketing Ethics Digest
Now that the technology’s first hype cycle is over, my top recommendation to companies is to have clearly defined goals and a clear ethical framework. Companies should invest in establishing an AI ethics council, creating an AI ethics policy, and carefully monitoring data and operations for ethics breaches, such as bias or misinformation, which could lead to reputational damage, breach of customer trust, and penalties and fines. Companies with a well-defined plan can avoid common pitfalls of unchecked AI use and instead leverage it as a sustainable, value-driven asset.
Gam Dias
Product Strategist, Hubbl Technologies
Author, The Data Mindset Playbook
Gen AI Readiness…
We’ve had AI for almost 20 years, but in business it’s been driven out of the IT organization, the engineering teams or the quants – that gave us the recommender algorithms, computer vision that powered self-driving cars, or algorithmic trading. AI is now accessible and much more understandable to the non-techy. So, it will show up in a number of places:
On the ground where employees are using these tools with no governance (and all the risks of IP leakage, hallucinations and unintended consequences), this needs to be managed and regulated so there are no surprises or lawsuits. IT organizations will have additional capabilities where they will be able to use Gen AI to build systems faster and with greater degrees of flexibility. The business will be able to create and deploy AI Agents.
But here’s where I have the most to say: Businesses are going to develop AI mostly to cut costs because that’s what seems the most appropriate use… increase profitability for lower investment. But there are other reasons. So, my first advice is to determine your AI strategy:
- Improve customer loyalty and retention
- Enable business operations to scale without adding additional costs
- Create cost-saving opportunities through headcount reduction •
Show that A.I. can be used to streamline operations without detrimental effects.
Then determine what automations you want to put in and how far along the spectrum to automate. Some processes need a human agent with AI in the background (e.g. emergency services), others can deal completely autonomously (e.g. schedule a package delivery). My tool Hubbl Process Analytics is designed to surface the process bottlenecks and identify the root cause, to find the low hanging fruit for automation in the Salesforce ecosystem.
Geoff Livingston
Chief Strategy Officer, CognitivePath
First, stop looking to OpenAI, other tech companies, and the larger AI trade conversation as the sources of what you can do with AI. Instead, look internally at your strategy and the biggest barriers your organization needs to overcome. Then ask yourself, are there elements of this challenge that an AI can help facilitate or strengthen? Then go out and see if there are possible solutions, AND look inside to see if your data, infrastructure and culture are ready to make it happen.
Stephanie Pereira
Chief Operating Officer, Astral
If you don’t already understand the capabilities, you need to ASAP. Companies using AI are reporting big boosts in efficiency. Exec teams who aren’t already should be getting educated on where businesses are already seeing huge return on investment. Teams who want to preserve headcount should host internal workshops to build capabilities, identify opportunities, and make a rapid-fire plan for putting ideas into action through testing. I love a micro-case study from Prodify’s Sara Zalowiz in which she talks about how a customer success management team integrated AI into their processes not to reduce headcount, but to increase efficiency and results.
Dr. Rebekka Reinhard
Founder & Editorial Director, human
Stop treating AI as a novelty or a trend that will pass sooner or later. Think of it as a tool to augment human capabilities in a co-intelligent way. Integrate Gen AI in a way that empowers workers, not replaces them. Don’t use AI as an excuse to fire people. Use it to make the business world a more humane place.
Greg Verdino
Chief Operating Officer, CognitivePath
At the risk of sounding like Simon Sinek: Start with why. Don’t start with what AI can do; start with why you’re using it in the first place. Generative AI can be a powerhouse for productivity and personalization, but there’s a risk that in the rush to automate, we end up with a lot of noise and not a lot of substance. AI works best when it amplifies human expertise rather than trying to replace it. So, if you’re just looking to check a box or keep up with the latest tech trends, you’re missing the point. Use AI where it can truly move the needle, and don’t sidestep the real challenges around data quality, transparency, and accountability. Those who get this balance right will set themselves up for success; the rest may find that AI isn’t a shortcut—it’s just the beginning of a bigger challenge.
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What will the next two years of the Generative AI revolution look like?
We asked 10 AI thought leaders peer into their crystal ball and predict what the next two years may bring. They saw a shift from experimentation to operational integration, a focus on agentic AI, and the need for increased regulation and responsibility. Many see parallels to previous tech revolutions like Web 2.0, with expectations of improved infrastructure, governance, and integration into existing software platforms. They also predict a move from individual use to enterprise-level implementation, even as leaders grapple with the organizational factors that stand between failure and success.
David Armano
CX Strategist & Enterprise AI Executive
There will still be a lot of adoption of GenAI in the SMB space, but over the next two years, we’ll see steady acceleration of GenAI innovation and integration within the large enterprise space. Enterprise AI will shift from being more of a thought leadership topic at the executive level—to something where large organizations really start making operational changes, whether that be in HR, marketing, product, sales, technology etc. It’s going to last a lot longer than two years, but we’ll see the shift from talking about it to doing something about it within the large enterprise level.
Courtney Baker
Chief Marketing Officer, Knownwell
It’s going to continue to move quickly. Expect off-the-shelf AI platforms at the operational level of the organization as well as regulation.
Shashi Bellamkonda
Principal Research Director, Info-Tech Research Group
All the providers of existing software will add AI capabilities to their software. Organizations will use multiple LLMs or custom LLMs to solve different use cases, companies that put all their eggs in one basket will need to reengineer their systems to connect to different LLMs. All AI generated content will be water marked either through legislation or companies opting to do this voluntarily.
David Berkowitz
Founder, AI Marketers Guild
The biggest change is likely to be around agents — proactive bots that both businesses and consumers use to accomplish specific tasks. That’s going to lead to a slew of challenges for marketers, with a lot of independent publishers serving most of their ads to bots instead of humans. Advertisers will then lose out on reaching some of those highly targeted audiences. It’s going to require new business models, and current leaders in both AI and advertising such as Google, Meta, and Amazon are likely to benefit the most, even as some of their legacy business models take a short-term hit.
Paul Chaney
Publisher, AI Marketing Ethics Digest
Over the next two years, the Gen AI revolution will most likely move from experimentation to deliberate integration. From tools that only help content production to sophisticated systems impacting product development, customer experience, and strategic-level decision-making, AI-powered solutions will become ingrained in daily corporate operations.
Companies will simultaneously be pressured to embrace more open and ethical AI methods as the regulatory environment develops. This will make AI ethics and responsible AI use even more critical as businesses seek direction to address changing criteria and build customer trust.
Gam Dias
Product Strategist, Hubbl Technologies
Author, The Data Mindset Playbook
I see the emergence and popularity of agentic systems such as Salesforce Agentforce where agents can be easily created and deployed.
It’s going to be like the web… today with Gen AI we are at the beginnings of Web2.0. There will be tools that democratize access and applications will flourish. Like when we moved from databases to ERP applications, there will be more infrastructure like Gentoro https://www.gentoro.com/ and governance like Bast.ai https://bast.ai/home. These tools will get absorbed into the stack over time, but the next 2 years we are going to see the transition from an innovation that businesses are playing with that is scaring the IT department and the lawyers, to something more robust and less risky.
Geoff Livingston
Chief Strategy Officer, CognitivePath
A renewed focus on pragmatic business applications will cause a shuffling of sector thought leadership with companies like Anthropic, Mistral and OpenAI becoming more traditional B2B suppliers. Leadership will be based on successes with the larger tech companies with their powerful enterprise client lists becoming market leaders. You can already see this happening with companies like Accenture, Amazon, and IBM in their positioning and increased media attention.
Oh, and the Agent AI thing? Expect another full-blown hype bubble.
Stephanie Pereira
Chief Operating Officer, Astral
Over the next 2 years, we are going from tinkering to operationalization.
We will move from a context that currently looks like ICs who have been relying on chat-based workflows to accelerate work to businesses that incorporate complex workflows into basic business processes. Instead of having to prompt and prompt again for results, AI will be integrated into every tool we use. The accuracy will get better and better, and integration will get more prevalent.
And not to state the obvious: Agentic AI is here — Anthropic rolled out Computer Use via API earlier this month, and even with this baby version, to me it has represented an unlearning in how I think and do. Forcing me to step back and find new pathways for solving problems and setting up teams and workflows.
Dr. Rebekka Reinhard
Founder & Editorial Director, human
I ain’t no fortune teller! But I hope that the focus will shift from innovation for innovation’s sake to solving concrete problems – whether in medicine, like cancer research, or in creative industries, like media. I also hope it will be a time of reckoning, when ethical considerations and regulatory frameworks catch up with technological advances. Questions about the role of AI in the public sphere – deep and shallow fakes, privacy, bias, agency – are likely to dominate the discourse. We’ll need to balance rapid technological adoption with the protection of fundamental human values. And we need an answer to the question that Nobel Prize-winning economist Daron Acemoglu keeps insisting on: “What do we want from machines?”
Greg Verdino
Chief Operating Officer, CognitivePath
Generative AI itself will no longer be a “revolution.” We may already be reaching “peak LLM” and – as impressive as they can be – generative AI tools alone rarely live up to their promise. The future won’t be about squeezing every last bit of performance from a single approach. It’ll be about building sophisticated hybrid systems that combine reactive, predictive, generative, and agentic AI – and probably other technologies altogether – to deliver holistic technology-driven solutions to increasingly complex challenges. Companies that make this leap will have a shot at seizing AI’s truly transformative potential. But here’s the kicker: if they don’t address their messy data, calcified culture, siloed structure, and “last century” strategy, AI won’t save them. It just might hammer the last nail into their coffin. And as demands for transparency and ethical use keep growing, those who dive in without a a clear North Star are in for a rude awakening. In the end, AI will either be your competitive edge or the mirror that reflects your biggest flaws.
