For decades, marketing technology has been geared toward improving efficiency and driving growth through data. Traditional tools like legacy automation tools and basic AI have helped marketers segment customers into groups, run routine tasks and manage ad spend. However, as the online world grows more complicated and customer behavior becomes less linear, these older tools are struggling to keep up. That’s where Agentic AI comes in. Agentic AI represents a new generation of intelligent systems that can set goals, learn and make decisions dynamically. So, how do these new Agentic AI tools compare to the old ones? Here’s a simple comparison.

Traditional marketing tools

Traditional marketing automation and AI tools follow a set of strict rules, like a flowchart. For example, “If a customer does X, then do Y.” Marketers have to set up every possible action and reaction. If someone clicks an email, the system might automatically send them a discount offer. If they don’t click, it either waits or tries to send another message. These tools work in static scenarios and falter when faced with unexpected data or shifting user behavior. They depend heavily on old data to make decisions and need people to check, update and guide them often.

Agentic AI

Agentic AI works very differently from older tools. Instead of just following a set of instructions, Agentic AI sets its own goals — like trying to get more people to buy something or interact with content — and changes its approach on the fly using real-time information from many sources. It acts like a digital helper that can think, plan, test out ideas and improve all by itself, always reacting to what's happening in the moment.

Why are brands and marketers switching to Agentic AI?

• Efficiency and scale: Agentic AI does a lot of work automatically. Marketers don’t have to swap ads, change bids every week or watch dashboards all the time. The AI handles thousands of campaign details quickly and at a scale people can’t match. Marketers just set rules and goals, and the AI takes care of the rest. This leaves marketers with more time for creative and strategic thinking
• Personalization: Old tools might just put someone’s name in an email. Agentic AI goes much further. It learns what people do, breaks audiences into new groups and creates personalized experiences by guessing what people want and need. This means offers are more useful, people pay more attention and customers stay loyal
• Better results: Companies using Agentic AI see clear improvements. They report customer conversion rates and campaign returns going up by 25-30% compared to older systems. The AI spots new trends quickly and adjusts, so results improve faster
• Adaptability: Old tools struggle when things change, like new channels or new rules. Agentic AI can think and adapt, so it works well even when the market shifts or customer habits change. It keeps marketing campaigns effective, no matter what happens

Are there any downsides or limits to switching to Agentic AI from traditional tools?

1. Agentic AI: Powerful, but needs guidance

Even though Agentic AI can do a lot on its own, it still needs clear goals, rules for what’s right and wrong and to work well with a brand’s strategy. Getting started with Agentic AI takes time and money upfront, plus teams need to learn new ways of working. Furthermore, it must be tested carefully to ensure it meets  business goals and follows the organization’s values.

2. Traditional tools: Dependable, but not very flexible

Legacy automation tools are still useful for jobs that don’t change much or for industries with strict rules, where you need things to be reliable and predictable. If an organization isn’t ready for AI that adapts on its own, these tools give a steady, but less flexible, way to manage work.

What is the future of technology in advertising?

Advertising is a very dynamic industry. As more people want personalized ads, brands that only use traditional tools won’t keep up. Agentic AI is a big step forward. It doesn’t just automate tasks; it facilitates achieving bigger goals across many campaigns at once. With the help of Agentic AI companies already see better results, like faster changes and smarter targeting.

In the future, success will come to brands and marketers who mix creative ideas with smart, fast-moving AI. Teams will need to learn new skills and work closely with these smart systems, treating AI as a helpful partner that can adapt and improve advertising in real time.

Based on the current market and trends, HCLTech’s AI and automation teams, along with experts from media industries, can help build smart AI agents for streaming platforms. These agents can automatically create ad revenue reports for marketers and agencies. Here’s how they work and what benefits they bring:

• Audience profiling agent: This agent finds out who is watching, their habits and what they like. It groups viewers (like “18-24 urban gamers” watching sci-fi shows) and shows which ads would work best for each group. This helps marketers target ads more accurately, which can raise ad prices by 20-30%
• Content performance agent: This agent checks which shows or movies are most popular and when people are watching. It recommends where ads will work best (for example, “Top 10 rom coms are perfect for beauty ads”) and gives clear data to help agencies place ads that make more money
• Ad optimization agent: This agent figures out the best type of ad, how long it should be and where to put it during a show. It tests different ad placements and predicts which will annoy viewers the least and get the most conversions. This means ads are more effective and marketers spend more on valuable ad spots
• Revenue forecasting agent: This agent predicts how much money ads could make on certain shows or campaigns. It looks at past results and outside factors like holidays to give clear forecasts, so marketers can plan their budgets and make decisions faster
• Competitive insights agent: This agent compares the streaming platform’s ad performance with other competitors. It highlights where the platform is doing better (like “25% higher engagement on sports shows”) and finds new trends. This helps marketers see why they should choose this platform for their ads
• Automated report synthesis agent: This agent pulls all the information together into easy-to-read, branded reports. It creates summaries, charts and templates that can be shared with clients. This saves sales teams time so they can focus on selling, not making reports

By using these AI agents, streaming platforms can better understand their viewers, place ads more effectively and earn more money from advertisers. The whole process becomes faster, smarter and more profitable for everyone involved.

How can this be achieved with respect to the technology stack used, data sources, costing and ROI projection? Please contact unmesh.khadilkar@hcltech.com for more information.