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Top 5 GenAI Predictions for 2025 and Impact on IT (from GenAI)

• By David Ramel
• 12/19/2024

Everybody has an opinion on just how far and fast this GenAI thing will go, and as a tech journalist I always get inundated with predictions from all manner of experts and pundits at this time of year.

But this year, armed with GenAI, rather than sift through the detritus I just asked GenAI itself. I asked five different online systems about their predictions for GenAI in 2025, which simply means (at this point anyway), they basically just round up all human predictions. Then, to get a consensual consensus, I asked for a synthesized top five, distilled from the longer lists.

From the headings on down, these five are surprisingly similar. These things don't seem to consult that many sources, so I thought limited scans would result in more varied responses. Here they are, in no particular order, with the summaries provided by ChatGPT's 4o model, supposedly the most "advanced" model at my disposal (company pays for it). I also had 4o summarize the impact of each prediction on enterprise IT.

Advancement of Multimodal AI
Generative AI will become increasingly capable of processing and generating across multiple data modalities (text, images, video, and audio). This advancement will enable richer, more immersive, and context-aware applications.

Impact: Enterprise IT will need to integrate and support AI systems capable of handling diverse data types, such as text, images, video, and audio. This will require updates to data infrastructure, enhanced storage solutions, and tools for managing multimodal workflows. Organizations will benefit from more contextually aware systems, enabling richer user interactions and advanced analytics.

Rise of Autonomous AI Agents
AI agents capable of performing complex tasks autonomously will gain widespread adoption. These agents will be used in areas such as customer service, task management, and collaborative workflows, enhancing productivity and operational efficiency.

Impact: Enterprise IT teams will play a critical role in deploying, monitoring, and maintaining autonomous AI agents. These agents will handle repetitive and complex tasks, reducing manual workloads for employees. IT departments will need to develop frameworks for managing these agents, ensuring secure and efficient operations while addressing concerns about autonomy and accountability.

Widespread Industry Integration
Generative AI will be deeply integrated into industries and enterprise tools, revolutionizing workflows and decision-making in sectors like healthcare, education, and creative fields. This integration will drive innovation and productivity across various domains.

Impact: The adoption of generative AI across industries will demand that enterprise IT teams adapt their technology stacks to incorporate AI solutions seamlessly. This could involve integrating AI into legacy systems, adopting industry-specific AI tools, and training staff to work alongside AI-driven processes. IT will also oversee the scaling of AI systems to meet operational demands while ensuring compliance with industry standards.

Ethical Considerations and Governance
With the proliferation of AI, there will be a strong focus on ethical considerations, regulation, and governance to address issues of bias, transparency, accountability, and misuse of AI technologies.

Impact: IT teams will need to implement robust governance frameworks for AI deployment, addressing ethical considerations such as bias, transparency, and accountability. This will include creating audit trails for AI decision-making, ensuring compliance with regulations, and building secure systems to prevent misuse. Enterprises will need to allocate resources to develop responsible AI practices, supported by their IT infrastructure.

Personalization and Human Augmentation
Generative AI will drive highly personalized user experiences and augment human capabilities. This will foster innovation, enhance creativity, and offer competitive advantages for businesses by tailoring solutions to individual needs.

Impact: Personalization in enterprise tools will drive the demand for AI systems that tailor experiences to individual users. IT teams will need to manage the underlying data processing and AI models that enable such personalization. This will involve deploying scalable and secure data pipelines, ensuring compliance with privacy regulations, and optimizing systems to augment employee capabilities and productivity effectively.

Stay Tuned
Next year I'll ask AI to reflect on how well it did. Actually, next year AI will be writing this, and your AI will decide if you should see it or not.