Legacy brands are falling behind in today’s AI-driven economy because they aren’t adopting modern intelligent processes fast enough. Meanwhile, AI-first startups are moving quickly by using real-time data and automation to redefine customer experiences.

As businesses undergo constant disruption, customers now expect instant, tailored services that traditional methods lack. Thankfully, legacy brands can turn this around. 

In this article, I’ll reveal how AI-first startups are taking the lead, challenges legacy companies face with AI adoption, and six best practices they can pick up today.

Comparing AI-First Startups and Legacy Brands

AI-first startups are companies that embed AI at the core of their product, operations, and culture. From product development and customer engagement to personalization and performance tracking, every aspect is driven by data and automation. 

A notable example is Tolstoy, an AI-native platform that powers interactive, shoppable video experiences at scale by adapting content in real time based on viewer behavior.

Legacy brands like Coca-Cola, Walmart, or Nike, on the other hand, built their operations long before AI emerged. Their systems were optimized for a different kind of market, one where speed, personalization, and real-time decision-making hadn’t peaked.

Today, many of these companies are trying to catch up by integrating AI into existing systems. It’s a start; however, they still position AI as an add-on rather than a primary driver. 

The Key Challenges Legacy Brands Face with AI Adoption

Several legacy brands have already invested time and resources into AI adoption. However, they experience some of these obstacles below: 

Old Systems and Infrastructure

Many legacy brands’ operations rely heavily on outdated tech stacks, which can’t handle real-time data or intelligent information, and this makes it harder to adopt modern AI tools.

Cultural Resistance and Slow Decision-Making

Legacy companies often follow slow, overly formal approval processes, making it challenging to roll out innovative solutions like AI. These brands can take months to approve new AI projects, or even abandon them entirely to play it safe.

Lack of In-House AI Talent or Expertise

AI adoption becomes difficult when employees have limited exposure to emerging AI technologies. Plus, top AI talent often prefer to join AI-first startups, where their skills are better utilized, valued, and rewarded.

Poor Data Quality and Siloed Teams

AI innovations rely on real-time, accessible data to function effectively. However, legacy brands often store customer data in outdated systems, like static Excel files or siloed databases, that are rarely updated and challenging to integrate.

6 Best Practices From AI-First Startups That Legacy Brands Should Emulate 

The rapid growth of AI-first startups is primarily attributed to their culture of starting early and their focus on using technology to enhance the customer experience. 

This has put them ahead in today’s ever-evolving market. Below are six of their best practices that legacy brands can adopt today to remain relevant in the future as the world evolves:

Test and Iterate Strategically

AI-first startups don’t wait for everything to be perfect before launching; instead, they test early, gather feedback quickly, and make adjustments continuously until things fall into place. 

There’s no time wasted on over-planning or getting stuck in protocol-heavy approval loops, which is often the default for legacy brands.

Legacy brands should adopt this approach by skipping long meetings and instead conducting small, rapid tests using tools designed for speed.

This fast and feedback-driven iteration saves time and helps you learn to serve customers faster, eliminating guesswork.

Put AI at the Core, Not as an Add-On

Let’s be real, some companies treat AI like a nice addition. They build a product, then try to add an AI feature like it’s an afterthought. However, that’s not how AI-first startups typically operate.

AI-first startups build their products and business operations around AI as their core. From product design to customer interaction and to backend decision-making, AI is involved in everything.

Legacy brands can also emulate this approach. A good starting point is using AI for eCommerce by integrating tools that save time, increase conversion rates, improve retention, and match the experience that customers expect.

Build a Culture That Encourages Continuous Experimentation and Adaptation

AI-first startups create an environment where ideas are tested early, data makes the decisions, and failure isn’t something to avoid; it’s how they grow.

But legacy brands? They’re often stuck behind layers of approvals, endless meetings, and a general fear of spoiling what works.

The good news is, you don’t need to overhaul your entire company overnight.

Start with something small. Run an A/B test on a landing page. Pilot a new onboarding experience. Try out an AI tool in just one campaign. These bite-sized experiments can lead to big wins.

Invest in Data Infrastructure for Decision-Making

AI is as effective as the data it receives. AI-first companies prioritize clean, unified, and real-time data pipelines that enable more intelligent decision-making. Legacy brands, on the other hand, often operate with siloed and inconsistent data scattered across teams.

A good first step is to audit your data. Is it centralized? Accurate? Accessible to those who need it? From there, introduce tools that can harness this data, like AI-powered analytics or customer behavior platforms.

Personalize Customer Experiences with AI

Today’s customers expect experiences tailored based on their behavior, preferences, and intent. AI-first startups deliver on this by using recommendation engines, dynamic content, and real-time insights into customer actions. 

Legacy brands can start by applying AI in small yet impactful ways, such as personalizing landing pages, stores,  or product recommendations.

Build or Partner for Talent

Every company can have access to AI talent without hiring a new in-house team. AI-first startups either hire or collaborate with professionals who understand both data and product development. Legacy brands can take a cue from that, and upskill their existing teams in AI literacy or partner with vendors for intelligent tools.

The Future Belongs to the Bold

Legacy brands don’t need to reinvent the wheel to stay competitive. What they do need is to learn from the fast-paced innovation and adaptability of AI-first startups. If you want to meet the demands of today’s market, you must begin by assessing your current AI readiness: where do your data, talent, and tools stand today? 

The journey starts with shifting your mindset, updating processes, and embracing new technology, one step at a time. It’s not about a complete overhaul overnight, but about making smart, gradual progress. Those who adapt will thrive. Are you ready to take that crucial first step?