State of AI 2025
Key Highlights
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AI is expected to contribute 2.92%–3.92% of global GDP by 2025, highlighting its growing impact; for context, agriculture accounted for 4.1% in 2023.
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Over 50% of generative AI models used by enterprises will be domain-specific by 2027, a sharp rise from just 1% in 2023.
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By 2026, 75% of businesses will create synthetic customer data, compared to less than 5% in 2023.
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GenAI is driving explosive growth, with the market expected to reach US$62.72 billion in 2025, growing at a 46.47% CAGR and reaching US$356.10 billion by 2030.
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By 2025 30% of GenAI projects are expected to be abandoned after proof of concept.
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Targeting the right audience is key: C-level executives and departments like Marketing, Sales, and IT lead GenAI adoption.
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AI-driven shopping tools enhance personalization, but human touch remains vital for addressing complex customer needs in 2025 and beyond.
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Despite the growing interest in AI adoption, a major barrier for companies is the lack of transparency in statistical validation and concerns over the accuracy of AI-driven solutions.
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9 AI trends to watch in 2025: synthetic data, automated insights, real-time data, data trading markets, behavioral data as the new gold, automation, micro LLMs, A2A adaptation, and generative AI revolutionizing government.
AI Market Overview for 2025
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In 2024, the AI market was valued at approximately US$184 billion, with a projected compound annual growth rate (CAGR) of 28.46% from 2024 to 2030, resulting in an estimated market volume of US$826.7 billion by 2030.
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In an optimistic scenario, AI is expected to contribute 3.92% of global GDP in 2025. Conversely, even under a more cautious estimate, this figure could stand at 2.92%. For context, agriculture accounted for 4.1% of global GDP in 2023, underscoring the rapid rise of AI as an economic driver.
The global AI market is set to increase by 32.61% from 2024 to 2025. What does this mean for you?
If you are an AI tool provider and observe a decline in your revenue, it may not be due to economic uncertainties, as the AI market continues to rise. Instead, the cause may be related to your product not meeting the needs of your customers, an unclear value proposition, not trustworthy or reliable AI solution, or it can be that you are not segmenting your market properly. It's important to re-evaluate whether you have adequate information about your customers, competitors, and the market you're operating in
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When setting objectives for 2025, consider this ~33% growth and use it as a benchmark to shape SMART objectives.
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From an industry perspective, the healthcare sector continues to emerge as a leader in AI adoption. However other industries are also greatly investing in AI solutions as shown in Figure 2.
Are you looking to enter the AI market but unsure where to start?
Newcomers need to decide whether to target the B2B or B2C market, as each operates under distinct dynamics. For example, in the B2B space, many companies are still in the exploration phase with AI solutions, meaning there isn’t yet strong brand loyalty to specific AI tools. However, industry-specific AI expertise is crucial, especially in sectors with significant investments in AI, such as technology, retail, and healthcare.
GenAI Predictions for 2025
The GenAI market is projected to reach US$62.72 billion in 2025, with a remarkable CAGR of 46.47% from 2024 to 2030, culminating in an estimated market volume of US$356.10 billion by 2030.
By 2025, 30% of GenAI projects are expected to be abandoned after proof of concept. Why? It often boils down to four major hurdles:
So, what’s the key to winning over skeptical investors?
When pitching a GenAI solution, it’s crucial to address investor concerns with clarity and foresight. Focus on:
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Transparent cost structures: Clearly outline the initial and ongoing expenses to avoid any surprises. Investors appreciate a well-defined financial plan that reflects the true cost of development, maintenance, and scaling.
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Quick wins with long-term value: Highlight how short-term milestones lead to long-term ROI. While many investors expect early returns, they also want to understand how the project evolves into a sustainable, long-term asset.
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Resilience through adaptability: Acknowledge the broader macroeconomic impact, such as geopolitical, economical and environmental factors that might influence the project’s trajectory. Investors value businesses that can pivot based on these factors, especially when considering risks such as inflation or political instability.
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Clear ROI path: While the Gen AI market shows huge potential, investors want to see measurable value within a reasonable timeframe. Quantify the benefits, not just in terms of revenue, but also in productivity gains, customer satisfaction, and market differentiation.
Understanding your target audience is essential in the AI software space. Research reveals key insights into who is adopting GenAI and what drives their usage.
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By Job Function: Marketing, sales, product and service development, and IT departments are leading the charge when it comes to GenAI adoption.
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By Job Title: C-level executives are the most frequent users of Generative AI at work. Senior managers lead the adoption of GenAI both at work and outside work. Midlevel managers, in contrast, dominate the use of GenAI outside work.
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By Generation: Gen X leads the charge as regular users of GenAI both at work and outside work, showcasing their adaptability and willingness to embrace AI for personal and professional purposes. Baby Boomers and Millennials surprisingly take the lead in using GenAI exclusively for work-related purposes.
What Does Effective Targeting for a GenAI Tool Look Like?
A strong example of well-targeted AI market segmentation is the B2B audience simulator tool, SaaSy, launched in 2024. This tool is specifically designed for the SaaS B2B market, helping companies better understand their target audience—businesses that purchase B2B SaaS solutions—by simulating their opinions and preferences. In terms of segmentation, by job function SaaSy primarily targets marketers and by job title the tool focuses on C-level executives. Moreover, SaaSy is strategically positioned as a cost-effective solution—it’s entirely free, a significant draw for organizations seeking value-driven tools without hefty upfront costs.
Business opportunities in GenAI Solutions
One of the main business opportunities in 2025 is the Need for Domain-Specific Models and Synthetic Data. By 2027, over 50% of GenAI models used by enterprises will be tailored to specific industries or business functions, a significant leap from the 1% in 2023.
By 2026, 75% of businesses are expected to use GenAI to generate synthetic customer data, a dramatic rise from less than 5% in 2023.
How AI is Reshaping Consumer Experiences and Trust
Relevant product recommendations top the list of benefits, showing a strong consumer demand for tailored experiences (Figure 3). However, human touch remains essential, as only 19% of consumers feel comfortable relying solely on bots for complex customer service needs.
How Can Businesses Integrate AI While Preserving the Human Touch?
AI is increasingly used to enhance productivity, personalization, and customer experience, particularly in areas like shopping, where consumers prioritize convenience. However, while AI is essential for efficiency, the human touch remains crucial throughout the customer journey.
AI can help automate tasks and analyze data, but human interaction is needed to understand emotions and psychological needs. To successfully integrate AI and human touch, businesses must conduct thorough consumer behavior research to gain insights into their audience's emotions and preferences. This approach allows businesses to use AI strategically, ensuring that human empathy is maintained where it matters most.
Navigating AI Policy and Regulation
Research results show that nearly half of surveyed organizations recognize the importance of explainability in AI systems, but only a fraction have implemented measures to achieve it, with most falling short of full operationalization.
In response to these risks, governments and regulatory bodies are stepping up to set clear guidelines. The European Union’s Artificial Intelligence Act (AI Act), which came into force in August 2024, is a pioneering framework designed to ensure AI is developed and deployed responsibly.
What is the takeaway for you as an AI tool provider?
A closer look at research from various sources reveals a clear contradiction. While many companies express interest in investing in AI, they also show resistance due to concerns about reputational risks, such as misinformation. This presents an opportunity for AI providers to address these concerns by offering transparent information about the accuracy of AI-generated answers, statistical validation for synthetic data, and the results of thorough testing. By doing so, you can build trust and enhance the perceived reliability of your AI tool, establishing a stronger position in the market. Additionally, clearly demonstrating compliance with necessary regulations helps mitigate perceived risks, increasing the likelihood of adoption and fostering a loyal customer base.
The biggest AI trends in 2025
AI is everywhere, reshaping industries, sectors, and business operations in ways we couldn’t have imagined just a few years ago. Its reach is universal, and its influence is only growing stronger.
Through careful analysis of the latest insights, we’ve pinpointed nine key AI trends that will shape the landscape in 2025:
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Demand for Synthetic Data
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Automated Insights
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Real-Time Data
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Data Trading Markets
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Behavior Data as the New Gold
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Automation & Infrastructure Development
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The Rise of Micro LLMs
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The Beginning of A2A (AI-to-AI Communication)
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Generative AI in Government
1. Demand for synthetic data
The first half of 2024 faced one of the biggest waves of data privacy regulations and personal data protection in recent years. While these initiatives came mostly from the EU, Google played a huge role in personal data protection and data privacy policy measures. This trend will continue to accelerate due to concerns over data breaches and advancements in generative AI. Such measures are mandatory to proactively evolve with AI and technological advancements, as well as to regulate data usage and protect user data.
Information is one of the most valuable assets we, as humans, have controlled over the centuries, and its value is increasing more rapidly than ever before. However, since data regulations are highly restrictive, the shift towards synthetic data usage and adoption will become a new and affordable trend for many businesses in 2025.
Market intelligence companies are competing fiercely in this emerging field. Several AI personas and AI research methods work with synthetic data, but the majority of these companies still rely on primary research, meaning they still need actual data from humans through surveys or interviews to replicate it synthetically. This means that these companies offer new methods at a high cost. Primary research still requires an investment of around €20,000 to €60,000, and only after that can synthetic data and methods be applied to replicate the primary research, which increases the cost by another €35,000 to €51,000, depending on the research company.
One of the most emerging companies that makes synthetic data accessible and affordable is Enaks Market Intelligence, which uses multi-layer data integration to develop synthetic data at a much lower cost by combining custom primary research or secondary research, industry statistics, and community-generated insights with generative AI to replicate consumer behavior data with greater accuracy. A great example of their approach is SaaSy, which is provided for free on their website. SaaSy is an AI persona simulator that helps companies in the SaaS industry generate synthetic data from their ICP with around 96% accuracy, based on the latest statistical validation from Enaks Market Intelligence, and includes over 200 stats and research from across the globe.
Synthetic data is a completely new trend that will have a huge impact on how we operate businesses, from marketing to sales, and even in product development.
2. Automated insights
Analysis-related tasks have always been somewhat neglected or less focused on in many organizations, as they do not provide direct financial benefits but rather an overview and diagnostic of our business and direction. We use analysis to detect certain patterns, identify gaps, and better understand how our business operates from both a micro and macro standpoint. Analysis—whether it's marketing, business operations, sales, CX, CS, etc.—is a challenging task that requires a deep understanding of statistics, data modeling, and large-scale model interpretation. Because of this, and due to the lack of human resources and time, many analyses and reports are full of errors that can lead our decisions down paths that could damage our business.
Because of these challenges, the automation of insights has become a main target for 2024 and 2025. Many AI models are trained specifically for this purpose, like Claude Sonnet 3.5 from Anthropic, which we still consider one of the best AI models for data analysis and modeling. Many software platforms launched since 2023 and focused on implementing automated insights into their product development roadmaps, with varying degrees of success.
Are we in an era where we can consider this done? Not necessarily. Due to the nature and complexity of data analysis from many perspectives, we can’t consider this step complete in 2024, and in many cases, it won’t be fully achieved in 2025 either. All of the current AI models are still not capable of performing complex data analysis and modeling without human involvement. Taking into account how businesses are operating in the tech field, this won’t be fully achieved yet. The good news is that by early 2025, certain models and software using current AI technology will be able to almost fully perform basic analysis with minimal error margins.
3. Real time data
2024 was a pretty challenging year, not just for businesses but for politicians too. It was also the biggest election year that our modern democracy has faced in an unprecedented way. All of these factors taught us a very important lesson: real-time data is non-negotiable.
We all see how real-time information can save us from making big mistakes, and social listening, as well as community-generated insights and analysis, will see a huge rise. While it sounds promising and many businesses have these features in place in one way or another, like OpenAI’s ChatGPT, Perplexity.ai, and many others, this technology is still not 100% there yet due to the vast amount of data that needs to be collected and processed. The biggest gap for many businesses is time.
The biggest challenge for businesses remains time—the race to analyze data in real-time without sacrificing accuracy. Addressing this gap will require not just better tools, but also a shift in how organizations prioritize and integrate real-time data capabilities. Those who master this balance will have a distinct edge in navigating the complexities of an increasingly fast-paced world.
4. Data trading markets
Data monetization will reach new heights in 2025 and 2026. Data-commerce and data trading will boom in the coming years, and digital footprints will become harder to obtain due to the data regulations.
Therefore, data selling markets will gain significant focus across many industries. Besides data trading, personal data monetization will gain new attention, and AI-generated outputs will play a crucial role in data trading and data interpretation.
5. Behavioral data will be the new gold in 2025
Consumer behavior data that focuses on hidden insights, such as sentiment analysis, psychological factors, personal motivation, social listening, and so on, will become the new norm in data analysis and marketing. A big reset is coming to the field of digital marketing, and a rebirth of traditional marketing methods will rise in 2025.
In 2024, many businesses realized that consumer insights provided from a digital marketing standpoint—something we've been used to for more than 15 years—are just not enough and no longer offer a competitive advantage. We will witness a new renaissance of marketing intelligence and consumer behavior research in 2025, and marketing intelligence companies will take over digital marketing agencies.
This new era of marketing will bring a fresh perspective for many businesses, with emotional-led tactics based on solid and fact-based consumer behavior data, requiring highly skilled data analysis, data modeling, and statistical analysis.
6. Automation & Infrastructure Development
In 2024, the CEO of OpenAI, Sam Altman, said that in the near future, we’ll witness billion-dollar companies powered by just one or a couple of people. More precisely, he mentioned, “In my little group chat with my tech CEO friends, there’s this betting pool for the first year that there is a one-person billion-dollar company. Which would have been unimaginable without AI and now will happen.”
This claim can’t be achieved without two important elements: AI and automation. These two key players will highly shape the way we operate and cooperate with businesses. While automation has always played an important role for businesses, in 2025 we’ll see a higher demand for this trend. From marketing automation to business operations, automation and generative AI will be a major focus of business investment for many organizations, with no exceptions.
7. The Rise of Micro LLMs
While giants like Anthropic, Google, Meta, Windows, and OpenAI lead the development of traditional LLM, smaller models are getting more attractions from small and medium sized enterprises. Big models are intriguing but Micro LLMs are more attractive for many businesses who are looking to invest in generative AI.
Micro LLMs simplify implementation and reduce computing demands, making advanced AI accessible to companies previously deterred by high costs or complexity. These tailored models offer better performance, greater accuracy, and fewer hallucinations. Their compact design minimizes environmental impact, strengthens data control, and enhances cybersecurity, enabling deployment in localized, segmented network environments with diverse security requirements.
8. The Beginning of A2A
The high demand for automation and the rise of Micro LLMs are gradually creating a completely new business model: A2A (Agent-to-Agent), which reflects interactions between AI agents and other autonomous systems.
As we develop increasingly complex and interconnected AI agents, the need for these models will grow significantly. The focus of this emerging model will be on how AI agents communicate, negotiate, and collaborate with one another to accomplish tasks or deliver value. Autonomous decision-making and real-time data exchange will play a crucial role in this model. Task delegation and feedback loops will also be essential components when discussing practical applications of A2A.
Examples of A2A Interactions:
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Supply Chain Management: AI agents handling logistics communicate with warehouse inventory systems to manage stock levels and optimize delivery schedules in real time.
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Financial Services: One AI system analyzes risk, while another evaluates market conditions, communicating directly to adjust investment portfolios.
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E-commerce: AI chatbots from various platforms collaborate to enhance cross-platform customer experiences, such as order tracking and price matching.
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Healthcare: Diagnostic AI communicates with treatment planning AI to optimize patient care.
For A2A to function effectively, an extremely stable ecosystem is required. This includes technologies such as APIs, interoperability standards, multi-agent systems (MAS), and federated learning.
A2A has the potential to redefine workflows across industries, particularly as AI evolves from isolated tools into interconnected networks of agents working collaboratively.
9. Generative AI in government
As AI continues to shape the landscape in 2025, the focus on AI governance and ethical AI solutions has become a cornerstone of technological innovation. With artificial intelligence playing a transformative role across industries, companies are increasingly adopting frameworks to ensure transparency, fairness, and accountability in their AI systems.
A major challenge for this year’s IT advancements is addressing biases in AI algorithms. Organizations are tackling this by implementing rigorous auditing processes and adopting inclusive data strategies to reduce disparities in AI-driven outcomes. Ethical AI efforts also include environmental considerations, with a push toward reducing the carbon footprint of AI models through sustainable computing practices.
Another significant development is the emergence of AI governance frameworks designed to regulate how AI is built, deployed, and managed. Governments and industry leaders worldwide are collaborating to establish standardized guidelines that balance innovation with societal well-being.
By embedding ethical principles into their operations, businesses not only minimize risks but also build trust with stakeholders, paving the way for long-term success in the rapidly evolving tech landscape of 2025.
FAQ
What are the key AI trends to watch for in 2025?
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AI governance, ethical AI, synthetic data usage, and advanced automation are expected to shape the business landscape in 2025.
How will AI impact businesses in 2025?
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AI will revolutionize business operations by enhancing data analysis, improving decision-making, and automating complex tasks, resulting in significant efficiency and cost savings.
What is the role of AI in data privacy and governance in 2025?
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As data privacy regulations tighten, AI will play a crucial role in helping businesses comply with these rules while ensuring transparency, fairness, and accountability in their systems.
How can businesses mitigate AI biases in 2025?
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Organizations are focusing on inclusive data strategies, robust auditing mechanisms, and developing ethical AI frameworks to address biases and ensure fairness in AI algorithms.
What is synthetic data, and why is it important for businesses in 2025?
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Synthetic data is artificially generated data that mimics real-world data. It helps businesses address data privacy concerns while enabling more affordable and scalable solutions for data analysis.
How will automation and generative AI transform marketing in 2025?
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Marketing automation, combined with generative AI, will streamline processes, enhance customer insights, and enable more personalized and efficient marketing campaigns.
Can AI models fully replace human involvement in data analysis by 2025?
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While AI models are advancing, complex data analysis and modeling still require human expertise. However, by 2025, AI will be able to perform many basic analyses with minimal error margins.
What challenges do businesses face with AI and automation in 2025?
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Businesses will face challenges related to the integration of AI with existing systems, data privacy regulations, the complexity of AI models, and the high costs of implementing AI-driven solutions.
How will AI affect job roles and employment in 2025?
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AI will automate many routine tasks, but it will also create new job opportunities in AI development, data analysis, and ethical AI governance, requiring a shift in workforce skills.
What industries will benefit the most from AI advancements in 2025?
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Industries such as healthcare, finance, retail, marketing, and logistics will see significant advancements due to AI's ability to enhance decision-making, optimize operations, and improve customer experiences.