The Steps To Becoming An AI expert in 2025:
It’s clear that Artificial Intelligence (AI) is rapidly transforming various aspects of business and technology, with an unprecedented pace of innovation, investment, and business adoption, even faster than the internet’s early growth. While some hype exists, the underlying momentum suggests significant changes are on the horizon.
Here are some key predictions and insights about AI .
Strategic Importance of AI:
Having a well-defined AI strategy will be crucial for businesses, potentially creating a significant advantage or leaving those without one struggling to catch up.
Workforce Transformation:
AI agents could lead to a substantial increase in workforce capacity.
Responsible AI:
The return on investment (ROI) for AI initiatives will be closely linked to the implementation of Responsible AI principles. PwC encourages businesses to start putting AI to work in a responsible way.
Value and Sustainability:
AI is expected to be a driver of value creation and contribute positively to sustainability efforts.
Accelerated Development:
AI has the potential to cut product development lifecycles in half.
Competitive Landscape Shifts:
AI will reshape competitive dynamics across industries.
The development and application of AI agents are central to this transformation. An AI agent is a system or program designed to autonomously perform tasks on behalf of a user or another system by planning its workflow and using available tools. These agents go beyond simple natural language processing, encompassing decision-making, problem-solving, interaction with external environments, and execution of actions.
The sources highlight various aspects of building and utilizing AI agents:
Autonomous Operation:
AI agents can be designed to run autonomously based on set schedules and perform actions like fetching data (e.g., Bitcoin prices) and storing it in databases.
Pipeline Creation:
Powerful AI pipelines can be built by linking various AI tools. For example, a video generation pipeline could involve using GPT-4o for idea generation, Flux for image creation, Kling for video generation, OpenAI TTS for voice-over, and FFmpeg for video editing, all automated,
Tool Integration:
AI agents can leverage various tools and APIs to perform tasks, such as CoinGecko API for fetching financial data, Brave Search API for retrieving information, and OpenAI API for language processing and function calling. Frameworks like CrewAI offer a wide range of tools, including Brave Search, web loaders, and database connectors
Function Calling:
Function calling allows AI agents to use external tools by generating structured data that can be used to invoke specific functions.
CrewAI Framework:
CrewAI is a framework designed for creating collaborative AI agents, where multiple agents with specific roles, goals, and backstories work together to accomplish complex tasks. This involves defining agents, assigning them tasks, and configuring the crew to run these tasks, potentially in sequence , CrewAI also offers a command-line interface (CLI) for managing crews
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Agent Design:
Crafting effective agents involves giving them well-defined roles, goals, and backstories to guide their actions and improve their performance
Agentic Design Patterns:
Several design patterns enhance the capabilities of AI agents:
Planning:
Enabling agents to create step-by-step plans before executing tasks leads to better responses, especially for complex reasoning tasks, Frameworks like CrewAI can automate this planning process.
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Reflection:
Allowing agents to review their past interactions and outputs to identify areas for improvement is crucial for self-correction and enhanced performance. This can involve the agent reviewing its own work or another agent providing feedback.
Human-in-the-Loop:
Incorporating human input at various stages of an agent’s workflow allows for steering the agent, providing feedback, and ensuring the output aligns with expectations. CrewAI simplifies adding human input to tasks.
LangGraph: LangGraph, an extension of LangChain, is designed for building stateful, multi-actor AI applications with cyclic computation, enabling the creation of more sophisticated AI agents capable of complex, multi-step tasks
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Reasoning Paradigms:
Different approaches exist for solving multi-step problems with AI agents, such as the ReAct (Reasoning and Action) paradigm, where agents think and plan after each action and tool response to decide the next step.
Applications Across Industries:
AI agents are being applied in diverse fields to automate repetitive tasks, enhance productivity, and allow human employees to focus on more strategic activities
Examples include:
E-commerce: Personalising shopping experiences and revolutionising operations
Legal Sector:
Document automation, legal data analysis, and case management optimisation, with companies like TTMS offering tailored AI solutions for law firms.
Défense:
Advanced C4ISR systems, IoT integration, operational automation, and support for drone development, with TTMS also providing solutions in this sector.
Content Creation:
Generating and editing videos by intelligently linking video clips based on labels and scripts
AI Search Engines:
AI is also powering search engines to provide more relevant results.
Frameworks:
Besides CrewAI and LangGraph, other frameworks like Semantic Kernel and Autogen are used for building AI agents.
To further your journey as an AI expert, consider exploring these areas in more depth:
Experimenting with AI Agent Frameworks:
Try building your own agents and crews using frameworks like CrewAI and LangGraph
Study Like Your Agentic
Design Patterns:
Understand how planning, reflection, and human-in-the-loop mechanisms can be implemented and improve agent performance.
Investigate Different AI Models:
Explore the capabilities of various large language models (LLMs) and their suitability for tailoring AI Agents for various different agent tasks
Learning about Tool Integration:
Take steps to understand how to connect AI agents with different tools and APIs to extend their functionality
Keep Up with Industry Trends: Stay informed about the latest advancements in AI, including new models, frameworks, and applications, such as those discussed in the “2025 AI Business Predictions: PwC”
By studying these sources and continuing to explore the evolving landscape of AI and AI agents, you can build a strong foundation to become more knowledgeable in this field.
