AI Agents, Consolidation and Widespread Enterprise Adoption? Oh My!
Part III of our Future of AI Series offers futurist visions of the sector.
Now that we are experiencing the post-hype wave realism of the AI movement, what does the long-term future hold for the sector? Will we see AI vendor consolidation, rapid enterprise adoption of AI and automations, and helpful software assistants? The concluding section of our two-year GPT anniversary post picks up the crystal ball to examine the future of AI and what it means for businesses.
Our 10 experts — including David Armano, Courtney Baker, Shashidhar Bellamkonda, David Berkowitz,
, Gam Dias, Stephanie Pereira, and Dr. Rebekka Reinhard — put on their futurist hats for this question. They saw a shift from experimentation to operational integration, a focus on agentic AI, and the need for increased regulation and responsibility.
Many of the experts 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. See their individual insights below.
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 and governance like Bast.ai. 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.