2025: Agentic AI. The Next AI Wave Isn't About Chat - It's About Getting Stuff Done

The tech industry is pivoting hard toward Agentic AI - systems that can actually do things instead of just talking about them. While 2023 was the year of chatbots, 2025 is shaping up to be the year AI starts doing things on its own. The Internet as we know it will disappear as we enter the Post Web era, where the fundamental fabric of online interaction transforms from attention-based to intention-based systems. This shift represents more than just technological progress - it marks a transition from humans browsing websites to autonomous agents executing tasks based on our intent.

The web will evolve from a space where we "Read, Write, Own" to one where we primarily "Delegate," with AI agents handling complex tasks and interactions seamlessly in the background. This new paradigm dissolves traditional boundaries between websites, apps, and agents, creating an infrastructure where machines and autonomous systems interact with each other on our behalf, fundamentally changing how we engage with digital services.

From today’s human interface for the Internet, primarily to interact amongst ourselves, to how machines and increasingly autonomous agents interact with one another on our behalf through intent based architectures- Outlier Ventures, Jamie Burke The Post Web

Autonomous agents are fundamentally reshaping human society in ways that extend far beyond mere technological advancement. Their impact is both transformative and complex, creating a delicate balance between enhanced capabilities and societal challenges.

The integration of autonomous agents has led to increased cooperation and prosocial behaviours in group settings. These systems are making our daily lives more efficient, from managing routine tasks to enabling complex decision-making processes.

They're quietly revolutionising how we live and work, promising to free humans from mundane tasks and screen time. The last weeks we have seen that autonomous agents are the the distant future, but they are here, right now.

1. The Big Three Make Their Moves

Google just fired the first shot in the AI agent wars with Gemini 2.0. Built on JAX/XLA, it comes with three game-changing projects.

Google Gemini 2.0 (December 2024)

• Released Gemini 2.0 Flash experimental with enhanced multimodal capabilities and improved performance

• Introduced Deep Research, an AI research assistant with agentic capabilities

• Launched Project Astra updates with improved dialogue and tool integration

• Released Project Mariner for browser-based human-agent interaction

Microsoft isn't far behind. They're targeting enterprise with Copilot Studio's new autonomous capabilities, having already deployed 700 updates and over 150 new features in 2024[3].

Microsoft Developments (Late 2024)

• Announced Copilot Agents with multi-faceted workflow capabilities

• Released ten pre-built agents for Dynamics 365 platform

• Launched enhanced Copilot Studio for building custom autonomous agents

• Introduced Magentic-One, a multi-AI agent system

OpenAI is about to enter the ring with "Operator" in January 2025 - an AI that can literally control your computer and perform tasks like coding and travel booking.

OpenAI's Upcoming Release

• Planning to launch "Operator" in January 2025

• Will feature autonomous computer control capabilities

• To be released as research preview and through API for developers

• Focuses on tasks like code writing and travel booking

Industry Competition

Other tech providers are entering the race: Salesforce's Agentforce is targeting one billion agents by end of 2025, while partnering with Google Cloud and IBM for cross-platform integration.

• Salesforce launched Agentforce, claiming to process trillions of AI transactions weekly

• Anthropic released Computer Use API for agent development

• Industry facing challenges with high-quality data for model training

2. The Numbers Tell the Story

The agentic AI market is projected to reach $30.89 billion in 2024, with a compound annual growth rate of 31.68%. Gartner predicts that by 2028, 33% of enterprise software will include agentic AI, up from less than 1% today.

The AI Agentic Market Size

Gartner emphasises: “Agentic AI will introduce a goal-driven digital workforce that autonomously makes plans and takes actions — an extension of the workforce that doesn’t need vacations or other benefits.”

3. Why This Time It's Different

Traditional AI writes emails and makes pretty pictures. Agentic AI can execute multi-step tasks without handholding and adapt to new situations in real-time.

Companies are seeing massive efficiency gains. Already, 60% of Fortune 500 companies are using Microsoft's AI solutions, with Lumen Technologies projecting $50 million in annual savings.

The Road Ahead

The market is expected to reach $367.68 billion by 2033. We're looking at:

- Industry-specific agents

- AI-to-AI collaboration

- Deep business tool integration

- Enhanced safety mechanisms

4. Key Challenges

The integration of Agentic AI presents a complex web of interconnected challenges that extend far beyond basic implementation concerns. Security vulnerabilities in autonomous systems represent a multi-faceted threat, including model inversion attacks that can extract sensitive training data, adversarial examples that manipulate AI decision-making, and backdoor attacks that can compromise system integrity.

1. Technical Vulnerabilities

Quality control in decision-making processes is particularly challenging due to the non-idempotent nature of agentic systems - the same input can produce different outputs across multiple attempts. This inconsistency makes it difficult to validate results and ensure reliable performance across autonomous operations.

2. Data and Privacy Concerns

Data integrity faces unprecedented challenges as agentic AI systems may leak sensitive information through their training datasets or operational outputs. Privacy leakage can expose personal data, trade secrets, or other confidential information, particularly in natural language processing models that generate text based on training data.

3. Operational Challenges

Workforce adaptation must contend with the "black box" nature of these systems. The limited understanding of internal workings makes it difficult to identify root causes of errors or failures. This opacity challenges traditional oversight methods and complicates troubleshooting efforts.

4. Security Implications

Enhanced cybersecurity risks are amplified by the autonomous nature of these systems. Hardware vulnerabilities can bypass software-level security measures, while API attacks can compromise the critical connections between AI systems and other software components. The challenge is particularly acute when integrating autonomous agents from different vendors, where disparate agents don't share a common purpose or security framework.

Not limited , but in summary key risks include:

• Security vulnerabilities in autonomous systems

• Quality control in decision-making processes

• Data integrity concerns

• Workforce adaptation issues

• Enhanced cybersecurity risks

When using AI agents, the threat surface expands to include the chain of events and interactions they initiate and are part of, which by default are not visible to and cannot be stopped by human or system operators. -Gartner-

5. The Bottom Line

The next phase of AI isn't about better chatbots - it's about AI systems that actually get stuff done. By 2028, at least 15% of day-to-day work decisions will be made autonomously through agentic AI. Companies that harness this capability will have a massive advantage. Those that don't risk falling behind in what's shaping up to be the biggest tech shift since cloud computing.

The catch? Safety testing in controlled environments will be crucial. As Gartner notes, robust guardrails are required to ensure alignment with providers' and users' intentions.

To address this, regulatory sandboxes and testing facilities are being developed to offer controlled environments for AI system refinement. These sandboxes allow for the development, training, and validation of innovative AI systems before market release, under the supervision of competent authorities. Moreover, businesses are adopting secure testing strategies, such as using dedicated Full Copy Sandboxes, to validate functionality and performance without impacting live processes.

This approach helps prevent service disruptions, data issues, and security breaches while allowing for early detection of bugs and vulnerabilities. As the adoption of agentic AI grows, with Gartner predicting integration into 33% of enterprise applications by 2028, organisations that invest early in both the technology and its safe implementation will be well-positioned to lead their industries.

6. The Transformative Character of Agentic AI

We are witnessing a radical, qualitative change in our relationship with technology. These agents represent the first time in human history where machines make autonomous decisions that directly impact human lives - from healthcare to transportation. Whilst we have seen this development in several science fiction movies, we are not prepared. As early as in 1968 2001: A Space Odyssey" presents HAL-9000 as an AI making autonomous decisions that directly impact human lives, demonstrating early concerns about AI governance and control.

This shift requires a global conversation about ethics, governance, and human oversight.

The future of human-agent interaction will likely depend on our ability to use their benefits while mitigating risks. Success will require careful consideration of ethical frameworks, security protocols, and social policies to ensure these powerful tools enhance rather than diminish human potential.

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