The Next Innovation – “The Top Tech Trends to Expect in 2026”
Episode Date: January 12, 2026
Host: Jennifer Strong (Situation Room Studios)
Guests: Jeff Wilser (AI Curious), Charlotte Gee (MIT Technology Review), Robert (Bob) McMillan (Wall Street Journal)
Overview
This episode explores the technological trends expected to shape 2026, with a special focus on the next wave of artificial intelligence (AI), agentic AI, its impact on cybersecurity, finance, energy, healthcare, defense, social trust, and the future of work. Jennifer Strong and her expert guests dissect the year ahead, highlighting both the promise and peril of emerging innovations, while grounding predictions in experiences from 2025.
Key Discussion Points and Insights
1. Agentic AI and Cybersecurity
- Rapid improvements mean agentic AI—software that makes decisions and performs tasks autonomously—is genuinely influencing cybersecurity.
- Initially, AI “hacking” seemed like hype; recent events (e.g., report of nation-state actors using LLMs for cyber activity) show a real and fast-moving transformation.
- New tools allow both red teamers (attackers) and defenders to speed up their work and tackle greater complexity.
- Increased “attack surface” raises risks before defensive tools can keep up.
Notable Quote:
“It’s like they’re getting an army of interns that are not terrible… things are going to move faster, maybe get a little more out of control.”
— Bob McMillan [03:14]
2. AI Progress and Disillusionment
- Significant hype has led to some disillusionment, as frontier models plateau and “hallucination” (AI making things up) hampers reliability for both positive and malicious actors.
- Uncertainty over whether further breakthroughs are possible without rethinking fundamental constraints, such as compute or data.
Quote:
“One problem that criminals and everyone else is running into is hallucination. If you can’t rely on these models... it limits their utility.”
— Charlotte Gee [06:16]
3. Agentic AI in Finance and Trading (Crypto as a Sandbox)
- Agentic AI is being tested in crypto trading due to laxer regulations.
- Experiments include “swarms” of AI portfolio managers handling different portfolios and risk profiles, potentially foreshadowing disruption in mainstream finance.
Insight:
“Crypto has far less regulation than traditional markets ... It's a Wild West experiment being played out in the real Web3 world.”
— Jeff Wilser [07:25]
4. Infrastructural Challenges: Chips, Energy, Data Centers, Water
- Local opposition to data center buildouts is rising, citing energy and water usage, as well as residential disturbance.
- Moore’s Law is ending, and further progress must come from software and architecture, not hardware miniaturization.
- Water scarcity for data centers is emerging as a flashpoint.
Quote:
“We’ve built ... data centers where there’s not enough water in addition to not enough power. That’ll be one of the key things we talk about.”
— Jennifer Strong [11:19]
“We can’t depend on Moore’s Law. ... Where are the improvements going to come?”
— Bob McMillan [10:28]
5. Measuring AI’s True Value
- Traditional benchmarks for AI progress have become meaningless; real value is found in “boring” automation gains in back-office work and healthcare logistics, though these are hard to quantify.
Quote:
“Even if the models never improve one bit, as companies and humans figure out how to work with them better, it’s possible we could see some actual legitimate benefits that are just tricky to measure with receipts.”
— Jeff Wilser [11:56]
“Benchmarks ... are completely broken. It’s much more about how people are finding this helpful.”
— Charlotte Gee [12:33]
6. Physical AI: Robotics, Hospitals, and Construction
- Phase one: Bureaucratic and clerical automation in healthcare; phase two: diagnostics, robotic surgeries (still on the horizon).
- Digital twins and drone monitoring in construction could improve safety and cut waste.
- Smart building management and AI-optimized recycling are expanding efficiency and sustainability.
Quote:
“For AI to be useful, it needs to become boring... it means it’s working.”
— Jennifer Strong [17:54]
7. Societal Attitudes—Risk, Trust, Tolerance
- Even minor incidents involving AI (e.g., Waymo self-driving car kills a cat [14:43]) spark huge media and social narratives.
- “AI allergy” is developing: some become wary of anything marked “AI”; others embrace it.
Quote:
“There’s this kind of societal back and forth … what is our tolerance for mistakes?”
— Bob McMillan [15:08]
“There might be a mismatch between the actual objective risk and what feels like risk ... our societal ‘taste’ for AI is still developing.”
— Jeff Wilser [16:56]
8. Defense, Robotics, and Automation in Warfare
- Defense tech, especially autonomous weapon systems (e.g., drones hunting individuals in Ukraine), is advancing rapidly.
- Raises profound ethical and geopolitical concerns.
Quote:
“We’re seeing massive growth and excitement in defense tech ... some is frankly really quite scary.”
— Charlotte Gee [19:50]
“How do we feel about robot armies?”
— Bob McMillan [21:06]
9. Growing Complexity as a Threat
- Ever-more complex agentic systems unintentionally aid hackers ("complexity is the ally of the hacker").
- Security and commercial imperatives often conflict; well-guarded systems may lose out in the marketplace.
Quote:
“If you take the time to produce a model ... you will lose the race to have the best model. Not a great incentive to build a secure product.”
— Bob McMillan [22:58]
10. AI’s Effect on Children
- Concern over AI “companions” for children and the potential effects on socialization.
- Some evidence that kids themselves are becoming more savvy and skeptical about AI, privacy, and bias.
Quote:
“If 9, 11 year olds are growing up where their best friend is not a real person, how does that impact development in social skills?”
— Jeff Wilser [23:57]
“Kids are asking the hard questions ... more savvy than most of us adults.”
— Jeff Wilser [26:17]
11. Information Slop, Trust, and Deepfakes
- As generative AI content (“slop”) improves, the risk grows that deepfakes and synthetic content could decisively distort public discourse, although a landmark event has not yet occurred.
Quote:
“As it gets better ... easy to fool everyone. ... I'm very curious ... when there's no objective truth anymore ... how does it change the world?”
— Jeff Wilser [27:06]
12. Quantum, Synthetic Biology, and the Next Convergence
- Quantum computing remains hyped, but practical applications, especially outside nation-state-level codebreaking, are still limited and expensive.
- All emerging tech—quantum, bio, etc.—are converging through advances in AI.
Quote:
“What is the path toward widespread use of [quantum]? ... It’s hard to imagine happening in a widespread way.”
— Bob McMillan [28:48]
13. Clean Energy, Climate, and Health Frontiers
- AI’s energy needs are catalyzing greater investment in clean energy (nuclear, solar).
- Advances in batteries and health technology (including weight loss drugs and data-driven personalized health) are promising.
Quote:
“There have been amazing advancements ... the world has the tools it needs to address climate change. It’s a question of will.”
— Charlotte Gee [31:11]
14. Work, Jobs, and the “Intern Effect”
- AI makes workers more productive but likely means fewer entry-level jobs, with downsizing via natural attrition before dramatic layoffs.
- Upskilling and reskilling efforts are not widespread; transition challenges loom large.
Quote:
“As companies figure out how to integrate AI ... it seems inevitable ... we don’t have to replace Frank and Jill.”
— Jeff Wilser [32:38]
“Having an intern at my disposal ... makes me wonder how things are going to be for the interns.”
— Bob McMillan [33:23]
Noteworthy Quotes and Moments
- Bob McMillan: “Complexity is the ally of the hackers.” [21:30]
- Charlotte Gee: “We’re kind of turning humans into robots so they can train robots ... It’s a really weird world.” [34:35]
- Jeff Wilser: “AI Sloth might be the death knell for social media—it doesn’t feel like you can believe anything you see.” [26:57]
- Jennifer Strong: “For AI to be useful, it needs to become boring.” [17:54]
Additional Major Trends to Watch
- AI Companions: Digital friends, colleagues, and assistants with heightened personalization and possible addiction risks. [34:11]
- Data as the New Oil: Intense corporate efforts to acquire broader, deeper training data—sometimes leading to odd jobs like “dishwasher opener” for robot training. [35:11]
- Publishing and Internet Models: Shift from search/links to direct answer models is upending the business of publishing and information access. [35:42]
Useful Timestamps for Key Segments
- Agentic AI & Cybersecurity: [02:06]–[05:08]
- Crypto, AI, and Finance: [07:13]–[08:46]
- Energy, Water, & Data Centers: [09:29]–[11:32]
- Benchmarks and Measuring Progress: [11:32]–[13:06]
- Healthcare AI & Robotics: [13:06]–[14:43]
- Societal Attitudes & Risk: [14:43]–[17:54]
- Construction, Smart Buildings, Recycling: [17:54]–[19:50]
- Defense, Robotics & Warfare: [19:50]–[21:18]
- Children & AI Companions: [23:57]–[26:57]
- AI Slop, Deepfakes & Information Trust: [27:06]–[28:35]
- Quantum, Synthetic Biology: [28:48]–[31:11]
- Jobs & Workforce Impacts: [32:13]–[34:04]
- Final Roundtable: Trends to Watch: [34:11]–[36:24]
Summing Up
This episode provides a grounded yet forward-looking synthesis of technological shifts to expect in 2026. From the profound transformation of industries through agentic AI, to the increasing societal anxiety over trust and the relentless search for new energy sources and data, “The Next Innovation” offers both a warning and a road map for innovators and leaders. The conversation is lively and occasionally wry—with a recognition that the most crucial advances might not be the flashiest, but the “boring” ones quietly changing the infrastructure of daily life.