Part II ChatGPT Impact: The Next Two Years in AI
What steps should businesses take to successfully incorporate generative AI?
Two years after the launch of ChatGPT, a realistic view generative AI is finally emerging. We asked 10 experts — including
, Courtney Baker, Shashidhar Bellamkonda, David Berkowitz, Ernest Chaney, Gam Dias, Stephanie Pereira, and Dr. Rebekka Reinhard — 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.