You’ve probably heard it—at conferences, in your social media feed, or from that one friend who’s always ahead of the curve. Agentic AI is everywhere right now. But here’s the question: Why now?
AI’s been part of the conversation for years, from chatbots answering basic customer questions to recommendation engines suggesting your next Netflix binge. But agentic AI? That’s a whole different beast. It’s not just following orders—it’s taking initiative, making decisions, and reshaping technology and how we work.
In this article, we’ll cover:
- What is agentic AI?
- How does agentic AI work?
- What the experts are saying
- What is the difference between agentic AI and AI agents?
- How is agentic AI shaping a new world?
- Agentic AI use cases
- What are some agentic AI tools?
What is agentic AI?
Agentic AI refers to systems that act autonomously—they don’t just wait for commands. Instead of being reactive like most traditional AI tools (which require user input to function), Agentic AI has its own objectives and actively works toward achieving them. They harness AI agents that gather information, make decisions, and take action, and use reinforcement learning to take feedback and learn from it.
Think of it like this:
- Traditional AI is like a smart assistant—you ask it to schedule a meeting, and it does just that.
- Agentic AI is like a proactive team member—it notices gaps in your schedule, books relevant meetings, and even suggests prep materials ahead of time.
Agentic AI can help you execute tasks without constant human interaction, prioritize and work towards specific outcomes, and evolve and improve as it receives feedback from the actions it takes.
How does agentic AI work?
Agentic AI is made up of five key components: perception, outcome, decision making, taking action, and learning.
- Perception: The first step is for the AI to gather information. This may include existing customer data, retrieving data from an API or database, or analyzing a user’s request through natural language processing (NLP). For example, AI can process a customer support ticket using NLP to extract key details such as sentiment analysis or how to classify the ticket.
- Outcome: AI requires a clearly defined outcome to assess whether its decisions are effective. For example, the goal might be to reduce customer support resolution time or increase email click-through rates.
- Decision making: Based on the data gathered in step one, the AI begins making decisions. By analyzing past campaign performance or historical customer support interactions, it can identify patterns on what might be the best action. For example, if the goal is to increase email click-through rates, the AI can evaluate which email tones and imagery were most effective for each customer in the past and use that insight to replicate successful results.
- Taking action: Once the AI makes a decision, it takes action—such as sending an email or responding to a customer via live chat.
- Learning: After taking action, the AI receives feedback to determine whether it achieved the desired outcome. This is where reinforcement learning comes into play—evaluating whether the decision was positive or negative. The AI then applies what it has learned to future decisions, continuously improving until it reaches the desired outcome.
What is the difference between AI agents and agentic AI?
With the rise of AI, many terms are being used interchangeably, making it essential to understand their distinctions. Agentic AI and AI agents are often confused, but they serve different roles.
As mentioned earlier, agentic AI refers to AI systems capable of making decisions and acting on them, allowing them to pursue complex goals with minimal human input. AI agents, on the other hand, are software programs designed to handle specific tasks. They use natural language processing (NLPs) of large language models (LLMs) to understand a user inputs and often require human input to initiate actions.
A helpful way to differentiate these terms is to think of AI agents as employees handling individual tasks, while agentic AI functions as a manager, orchestrating multiple AI agents to achieve your desired outcomes. To help you understand further, here is a table highlighting some of the forms of AI.
What the experts are saying
There’s a lot of hype around agentic AI, but actual AI experts are all saying the same thing. That it will not only transform business, but also the way we live our daily lives.
Jensen Huang, the CEO of Nvidia, says that we are entering “the age of AI agentics” and in a presentation at CES 2025, Huang discussed the rise of AI Agentics, calling it “a multi-trillion-dollar opportunity.” He also emphasized that AI agents will introduce new digital workflows, fundamentally transforming the way we work.
Scott Galloway, Professor of Marketing at NYU's Stern School of Business, says “Boring jobs will be the first to get specialized by the agentic layer. The AI applications: Customer Service, Data processing, Coding Assistants, Contract Analysis, Compliance, Accounting”
Tejas Manohar, the CO-CEO of Hightouch, a leading agentic AI marketing platform, has said that “In the future, agentic AI will own marketing campaign execution. Marketers will focus on high-level strategy, while AI will handle the tactical work. Instead of A/B testing “journey A” vs. “journey B” or debating if “customer lifetime” is a useful segmentation metric, AI agents will create personalized journeys for every customer—continuously adjusting based on what they learn from individual behavior and broader customer patterns.” Tejas explained how agentic AI will provide insights that enable better decision-making than humans and even execute tasks autonomously and effectively eliminating the need for A/B testing or debating whether segmenting customers based on lifecycle is truly impactful.
It’s clear that AI has created a ripple effect and will transform the world. But this technology is new but there’s a reason why every tech company is racing to win the AI marketing.
How is agentic AI shaping a new world
The rise of OpenAI’s ChatGPT and other generative AI has profoundly impacted the world, boosting productivity, reducing operational costs, and more. But the AI revolution doesn’t stop there. In an era of agentic AI, businesses will operate more efficiently and deliver exceptional customer experiences, ultimately driving higher revenue.
The reality is that many business departments rely on inefficient processes. Take lifecycle marketing, for example—journey orchestration is often too rigid, and customers rarely follow a single path, instead belonging to multiple overlapping decision journeys. Testing, too, remains a slow, manual process, limiting teams to experimenting with only one variable at a time.
And that’s just one component of one department. Paid media teams struggle with manual budget allocation and performance optimizations that AI can automate in real-time. Sales teams spend hours qualifying leads instead of engaging high-value prospects. Finance teams still rely on static forecasts when AI could dynamically adjust models based on real-time data.
But it’s not that the old way was wrong—it worked. We simply didn’t have the technology to optimize these processes. Until now.
Agentic AI is the key to unlocking efficiency across your business. Tasks that once consumed valuable time—such as A/B testing in marketing, lead scoring in sales, or fraud detection in finance—can now be handled autonomously by AI. This frees teams to focus on high-level, strategic initiatives that require human expertise, like developing new market strategies, innovating products, and strengthening customer relationships.
Beyond just saving time, AI-driven tasks are also more efficient. With reinforcement learning and the ability to scale beyond human capacity, AI delivers superior performance, consistently driving better outcomes.
As agentic AI gains traction in business, early adopters are already gaining a competitive edge. It won’t be long before this becomes an AI arms race that you wish you had joined earlier.
Benefits of agentic AI
With agentic AI, you can eliminate the need to perform certain tasks yourself, freeing up your time while unlocking a range of benefits.
- Increased efficiency and productivity: Agentic AI can repeatedly perform tasks without fatigue, maintaining the same level of accuracy whether it’s the first or thousandth time. AI remains consistent and reliable unlike humans, who may become fatigued and prone to errors.
- Improved decision-making: By analyzing large datasets and conducting large-scale experiments, agentic AI can make informed decisions and continuously refine its approach based on real-time learning.
- 24/7 operations: Agentic AI can function continuously without breaks, making it ideal for tasks that require constant availability, such as customer support. Its ability to provide instant responses and resolutions enhances customer satisfaction and strengthens brand loyalty.
Agentic AI use cases
Agentic AI can be applied to any situation with clear inputs and outputs. The inputs for the AI to help make decisions can be customer preferences, lead scores, service tickets, or invoices. The outputs are the business goals you aim to achieve—increasing email click-through rates, closing more deals, or reducing customer resolution time. Here are some common use cases broken down by department to explore agentic AI in action.
Marketing
Running a campaign for a single person is simple—you can easily understand their needs and craft a personalized message. But when you scale this to thousands or even millions, that level of fine control disappears, often resulting in generic personalization and underwhelming results. With AI, you eliminate this problem by enabling true 1:1 personalization at scale, allowing it to engage with each customer individually and tailor interactions in a previously impossible way.
- Lifecycle marketing: Traditional marketers manually send emails, SMS, and push notifications to drive engagement. AI automates this by selecting the best message, channel, and timing for each customer, optimizing content in real-time based on behavior. Example: If a customer buys running shoes, AI recommends complementary gear, offers discounts, and adjusts follow-ups based on engagement.
- Onsite & in-app experience optimization: Traditional sites show the same content to everyone. AI personalizes experiences by displaying the most relevant banners, product features, and messaging in real time, increasing engagement and conversions.
- Paid media: Running ads across Google and Facebook is complex—balancing targeting, content, and budget. AI automates audience testing, budget shifts, and real-time adjustments, ensuring efficient spending. Example: AI reallocates budget from weak ads to high-performers, freeing you to focus on creative and strategy.
Sales
Sales teams face constant pressure to meet targets while managing lead generation, outreach, and deal closing. Repetitive tasks consume a significant portion of their time—researching prospects, sending outreach messages, qualifying leads, and managing follow-ups. While necessary, these activities divert focus from high-value relationship-building and closing deals. Agentic AI is a powerful force multiplier, automating routine tasks, enhancing personalization, and providing real-time insights to boost conversion rates. By handling the heavy lifting, AI allows sales professionals to focus on what they do best—selling.
- Automated outreach: Traditional outreach is repetitive—researching prospects, personalizing messages, and facing constant rejection. AI automates research, crafts tailored messages, and learns from responses to optimize outreach for better results.
- Lead qualification: Traditional outreach relies on guesswork and lead scores. AI analyzes data and external insights to identify high-potential customers, then crafts the ideal message to maximize engagement.
- AI sales assistant: Sales teams juggle tasks while chasing deals, often neglecting admin work. AI handles prospecting, follow-ups, and real-time sales support, freeing you to focus on closing.
Customer Support
Providing great customer support is challenging, especially when managing high inquiry volumes, diverse customer needs, and the pressure to maintain a consistent experience. Traditional approaches—scripted chatbots, static FAQs, and human agents with limited capacity—often fall short. The result? Long wait times, frustrated customers, and overworked support teams. Agentic AI revolutionizes customer support by dynamically understanding and resolving issues in real time. It reduces the workload on human agents while delivering faster, more personalized responses, ensuring a seamless customer experience.
- Chatbots: Traditional bots follow rigid scripts, leading to robotic interactions. AI uses your knowledge base and real-time context to deliver natural, personalized responses.
- Self-service knowledge centers: Static FAQs are hard to navigate and outdated. AI delivers real-time, relevant answers and keeps knowledge bases continuously updated.
- Voice AI for call centers: Agents juggle multiple cases, causing delays and inconsistency. AI handles initial inquiries, resolving issues or escalating them efficiently.
HR
Managing human resources is complex and time-consuming. HR teams handle recruitment, onboarding, compliance, and employee engagement—all while maintaining fairness and efficiency. Traditional processes, however, are often manual, slow, and susceptible to human bias. Agentic AI streamlines HR operations by automating routine tasks, improving decision-making, and enhancing employee experiences through intelligent recommendations and proactive insights.
- AI recruitment assistant: Sorting resumes and scheduling interviews is time-consuming. AI screens applicants, matches them to roles, and conducts initial interviews.
- Employee onboarding: Disorganized onboarding causes disengagement and turnover. AI personalizes training, answers questions in real time, and adapts learning paths for each role.
- HR policy and compliance monitoring: Manually tracking labor laws and policies is complex. AI monitors regulations, flags risks, and keeps employees informed.
Finance
Finance departments are weighed down by tedious, repetitive processes such as managing expenses, conducting audits, and handling accounts payable. Manual workflows create inefficiencies, increase the risk of errors, and pose security concerns. Agentic AI streamlines financial operations by automating workflows, detecting anomalies, and delivering real-time insights—allowing finance teams to focus on strategic decision-making rather than administrative tasks.
- Automate expense management: Manual reviews are slow and error-prone. AI automates classification, flags anomalies, and enforces spending policies in real time.
- AI-powered audits: Manual reviews are slow and labor-intensive. AI detects anomalies in real time, reducing audit time and improving accuracy.
- Accounts payable: Invoice processing is time-consuming. AI validates suppliers, tracks payments, and optimizes schedules to boost efficiency and cash flow.
Agentic AI tools by team
Now that you understand the benefits agentic AI can bring to different departments in your company, you might be wondering how to implement it. Fortunately, various AI solutions are available to help you get started.
Marketing
Marketing departments leverage AI marketing tools to automate and optimize campaigns, personalize customer interactions, and analyze vast datasets for actionable insights.
- Hightouch is an AI Decisioning tool that integrates with your data warehouse or customer data platform (CDP) to continuously optimize your marketing efforts through AI-driven experimentation and 1:1 personalization. The tool refines decisions based on customer interactions, improving outcomes like lifetime value and open rates. Providing full transparency into every decision enhances strategy refinement while eliminating the need for manual A/B testing.
- Albert.AI is an AI-driven platform that autonomously manages and optimizes digital marketing campaigns across various channels. The solution analyzes data in real-time to adjust strategies, allocate budgets efficiently, and enhance ROI.
- Smartly.io is a social media advertising platform that utilizes AI to automate ad creation, testing, and optimization. The platform streamlines workflows and ensures ads resonate with target audiences, reducing manual effort and improving performance.
Sales
Sales teams are adopting agentic AI tools to enhance lead generation, streamline customer relationship management, and forecast sales more accurately.
- Salesforce Einstein GPT is an AI-powered CRM assistant that integrates generative AI to provide personalized sales insights, automate tasks, and generate tailored communications, thereby improving customer engagement and sales efficiency.
- Claude for sales is an AI assistant designed to help sales professionals by analyzing customer interactions, providing real-time suggestions, and automating routine tasks, leading to more effective sales strategies and improved client relationships.
- Pipedrive is a sales management tool that incorporates AI to predict sales trends, prioritize leads, and automate administrative tasks. It enables sales teams to focus on closing deals and nurturing relationships.
Customer Support
Customer support departments utilize agentic AI to provide instant help, resolve issues proactively, and enhance overall customer satisfaction.
- EMA is an AI-driven customer service platform that autonomously handles inquiries, learns from interactions to improve responses, and seamlessly escalates complex issues to human agents when necessary.
- Zendesk integrates AI to provide automated responses, categorize tickets, and offer predictive analytics, helping support teams manage high volumes of inquiries efficiently and improve response times.
- DigitalGenius is an AI platform that combines machine learning with customer service operations to automate repetitive tasks, provide accurate responses, and free up human agents for more complex issues.
HR
HR departments embrace agentic AI tools to streamline recruitment, enhance employee engagement, and effectively manage talent.
- Workday uses AI to streamline HR processes, from talent acquisition to workforce planning. Its AI-powered recruiting assistant helps HR teams identify top candidates by analyzing resumes, predicting job fit, and reducing unconscious bias.
- Fetcher is an AI-powered talent acquisition platform that automates candidate sourcing, outreach, and pipeline management, enabling HR teams to focus on strategic decision-making.
- Deel is an AI-powered global payroll and compliance platform that automates hiring, onboarding, and payments across multiple countries. Its agentic AI streamlines workforce management by ensuring compliance with local labor laws, generating contracts tailored to each jurisdiction, and automating payroll processes.
Finance
Finance departments are implementing agentic AI to enhance risk assessment, automate financial reporting, and ensure compliance with evolving regulations.
- Arya.ai provides AI solutions for financial institutions, including risk modeling and predictive analytics, helping in making informed investment decisions and managing financial risks effectively
- Zest AI specializes in AI-driven credit underwriting, offering models that assess borrower risk more accurately and inclusively, improving loan approval processes and reducing defaults.
- Trullion is an AI-powered accounting platform that automates financial workflows, ensures compliance with accounting standards, and provides real-time visibility into financial data, enhancing transparency and efficiency.
Closing thoughts
If you're not thinking about how to implement agentic AI, your competitors are, especially in marketing. Whoop is seeing a 10% increase in their upsells. Agentic AI is the key to unlocking 1:1 personalization at scale and that's exactly what companies are using Hightouch for. If you're interested in learning more about how AI Decisioning can help you unlock and enable 1:1 personalization at scale, book a demo with one of our solution engineers to learn more.
