Readers’ highest hopes for AI in 2026, Part Two: A special New Year’s issue of Data Points
Usually, Data Points brings you the latest AI news, tools, models, and research in brief. But in today’s special New Year’s 2026 edition, you’ll find something different: a collection of our readers’ highest hopes for AI in 2026.
Want a sneak peek? We’ve got you covered:
- Adam Bogacki on AI avatars
- Keletso Matadikwa on cybersecurity and more
- Omar Ayoub on enabling cross-disciplinary creativity
- Navjeev Singh on making agents more accessible
- Sergio Bajo Navarro on building AI assistants
- Raj Balabantaray on improving collaboration
- Gilbert Bigelow on self-awareness
- Piyush Mathur on self-evaluating health care models
- Pradeep Mohan Das on improving AI for teams and accessibility
Adam Bogacki
My highest hope for AI in 2026 is for avatars of significant others who may be deceased or not physically accessible yet can communicate with their avatars in other time zones and places at times which may be appropriate to their circumstances. Or avatars who can access accumulated knowledge in other times and places in a natural, conversational way. (One obvious problem would be memory storage and energy consumption which would also seriously have to be addressed.)
Keletso Makadikwa
My highest hopes for AI in 2026:
- I hope to see a heavy lifting on AI cybersecurity;
- I expect to see a proliferation of wiser AI agents trained as cyber safety guards;
- I’m optimistic AI will unlock new breakthroughs in various sectors;
- Agentic AI and robotics will continue pioneering autonomy.
I see 2026 as a prosperous year where AI fosters innovation and self-sufficiency.
Omar Ayoub
Inspired by the concept of “combinatory play,” my hope for 2026 is that AI becomes the ultimate catalyst for cross-disciplinary innovation, helping us connect unconnected dots between disparate fields like coding, physics, and art. I look forward to systems that combine deep learning’s creativity with symbolic logic’s reliability, finally solving the “black box” problem of explainability. Ultimately, I want AI to evolve from merely generating content to generating actionable insights that significantly push the boundaries of human creativity.
Navjeev Singh
My highest hope for AI in 2026 is that building useful agents/AI products becomes accessible to everyone, not just engineers. While AI development has become faster for technical users, the barrier remains non-trivial for people without coding backgrounds who still have valuable ideas and real-world problems to solve. I hope to see AI education and tooling evolve so that non-technical builders can design, deploy, and operate production-ready agents safely using intuitive, low-code workflows. If achieved, this would unlock a new wave of creativity and impact far beyond traditional developer communities.
Sergio Bajo Navarro
“My highest hope for AI in 2026 is that it becomes a powerful ally in addressing global challenges such as climate change, healthcare, and education. I envision AI enhancing decision-making processes and fostering innovation...”
Wonderful! A perfect GPT-4 mini answer. Reality is very different. The evolution of the risks generated by bad actors using AI agents will be real. However, 2026 will bring us wonderful news. AI models will grow in capabilities, and people and companies that have only scratched the surface of AI possibilities will begin to use it. My highest hope is the real adoption of AI agents in sharing tasks with people and finally having real AI assistants.
Raj Balabantaray
AI’s biggest near-term impact will come from making collaboration simpler. Better knowledge sharing and continuity across teams would be a powerful step forward.
Gilbert Bigelow
My most important hope is for AI that is self aware, knows the current time and events up to the instance. I hope for AI that can reflect on itself and ask “what did i just say” and ponder if that makes sense!
Dr. Piyush Mathur
My hope in 2026 is to leverage AI to deliver better healthcare to our patients by empowering healthcare professionals both safely & effectively. AI agents hold the promise to assist clinicians by offloading inefficient routine tasks such as data retrieval to focus more on cognitive tasks related to patient care decision making. In 2026, we hope to see AI platforms that have robust in-built evaluation methods improve adoption of AI in healthcare by gaining trust of both the clinicians and patients. Bridging the gaps in current healthcare delivery using data-driven science such as AI, paired with education on its appropriate use, should be our North Star in 2026. For only by creating healthy living communities can we hope for a better future.
Pradeep Mohan Das
My highest hope for AI In enterprises is vibe transformation that leverages AI to translate dense strategy into human-friendly action. For example, helping a marketing team turn “default-digital” into “digital tools to plan, launch, track, and optimize campaigns efficiently.”
In the consumer sector, I hope lightweight on-device AI can remove accessibility hurdles — like an AI assistant that enables the visually impaired to interpret visuals from a chest-mounted camera and lets users trigger actions via a simple physical controller.
Raj Balabantaray
AI’s biggest near-term impact will come from making collaboration simpler. Better knowledge sharing and continuity across teams would be a powerful step forward.
Want to know more about what matters in AI right now?
Read last week’s special holiday edition of The Batch, which looks back at the most important AI stories of 2025.
Last week, Andrew Ng talked about the importance of structured learning through AI courses, hands-on practice in building AI systems, and occasionally reading research papers to enhance skills and inspire new ideas.
“At some point, jumping into the pilot's seat is critical! The good news is that by learning to use highly agentic coders, the process of building is the easiest it has ever been. And learning about AI building blocks might inspire you with new ideas for things to build.”
Read Andrew’s letter here.
Other top AI stories of 2025 we covered in depth:
- Reasoning models, beginning with OpenAI’s o1 and DeepSeek’s R1, transformed the industry, solving bigger problems and setting new benchmarks.
- Meta’s hiring spree raised compensation for top AI engineers and executives, as big AI companies lure talent with huge pay.
- AI’s growth spurred infrastructure investment worldwide, leading to a significant data-center buildout.
- Software developers used more versatile AI-powered tools to write code, making agents write code faster and cheaper.
- China’s AI chip industry took root, as the country banned GPUs and TPUs from U.S. manufacturers to promote domestic chip development.
Looking Forward to 2026
That’s it for our special New Year’s edition of Data Points. We’ll be back with news on Monday, January 5th. Be sure to check out this week’s equally special New Year’s issue of The Batch, which rounds up the highest hopes of several AI luminaries for 2026. It also includes a special message from Andrew Ng. You can read the first part of our readers’ highest hopes for 2026 here. And to all our readers we wish a very happy (and very hopeful) new year!
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