February 10, 2025The surge in generative artificial intelligence (AI) adoption has triggered a frenzy, with companies rushing to integrate AI into their products. But is this sustainable or just a trend?
AI advancements have been monumental across industries worldwide, with businesses integrating features to drive innovation and efficiency. While this has democratized access and allowed AI to become part of our daily lives, companies must think critically to use it effectively and extract its true value without getting swept up in the current rush.
The appeal of low-hanging fruit
Businesses have been jumping on the AI trend by leveraging large language models (LLMs) and integrating basic AI functionality into their offerings. This can look different depending on the organization, but it generally takes the form of chatbots that use natural language processing (NLP) and AI models to mirror human-like interactions with high context awareness. The ease and broad application of these programs have spurred businesses to implement AI wherever possible.
Integrating AI into many platforms has generally been a good thing, as quick AI wins have many benefits. These tools can simplify user experiences, enhance digital products using automation or prompts and streamline operations, reducing the need for constant human intervention.
This approach can help explore AI's capabilities and allows for initial experimentation without getting overly technical and complicated. However, this simplified version has limitations, as it barely scratches the surface of AI's potential capabilities.
The pitfalls of trend-chasing without strategic foundations
Applying trendy AI functions won’t guarantee a competitive advantage. Off-the-shelf solutions lack customization. Tailored solutions that don’t involve AI can sometimes address specific needs more effectively.
Everyone using generic AI programs leads to market oversaturation. If all businesses use the same tools, they have the same capabilities and offer the same services or experiences, making it harder for consumers to differentiate between the options.
Customers are now looking for more than just basic, trendy AI features and have clued into the fact that sustainable differentiation comes from a deeper strategy. The lack of that long-term value is displayed, and people are starting to notice the lack of foundation and integrity employed by these "one-size-fits-all" AI models.
Where the true value lies
Go back to first principles
Rather than deploying AI tools for novelty, consider why your business needs them. Revisit the original friction points. Then, research bespoke AI or machine learning programs that can address these issues.
Data and model assets as the foundation
The advancements in AI and machine learning make the investment worth it for businesses. While developing AI models takes time and resources, investing that into creating and refining custom programs ultimately leads to greater success down the line. Businesses would no longer rely on generic programs like their competitors, but would feature a setup unique to their needs.
There’s a potential for great success if businesses can leverage proprietary data as another differentiator from the competition. Companies that access their unique data sets gain unique insights, which they can use to train machine learning models to be more accurate and relevant to their specific goals. Focusing on data and model development helps businesses create AI solutions that aren’t just reactions to trends but are tailored to their unique needs.
Workflow integration
More often than not, businesses are extraneously integrating AI into the workflow. When done right, AI will be natural and integral to the core workflow of the user and autonomous. This is where we start to see the evolution from chatbot or co-pilot—which still rely on human interaction—to agents that can plan, perform tasks and achieve goals autonomously. That is where true value creation happens.
The future of AI
Customers should focus not just on the newest industry trends but also on the long-term implications of such trends. Rather than getting caught up in the flashiness of trend-chasing, take a look and focus on the "secret sauce"— the unique recipe and curation of data, models and strategy. That’s what we focus on at AdRoll. We started building machine learning into our bidding and insights platform before it was cool and have since been able to collect almost two decades’ worth of data from online behavior. This has helped us build a strong foundation with AI and will ultimately help our platforms outlast the hype.
As is typically the case, true value in the machine learning industry is derived not from trend adoption but from thoughtful and curated AI implementations. Consider the importance of having a specific strategy. That allows AI to be used to its fullest potential, encompassing data acquisition and model development into the implementation of the programs. Bespoke customization also allows for continuous improvement as the industry continues to evolve. Businesses should be committed to continuous improvement, allowing for adjustments and enhancements along the way.
Thoughtful AI integration as a path to sustainable growth
Getting started with a complex and growing technology like AI can be challenging, so sometimes, using simple machine learning programs as a gateway can be smart. There are benefits to using off-the-shelf programs to uncover your unique AI needs, but you should also recognize when you have outgrown that. Businesses must continue evolving and refining their use of machine learning to build complex, defensible strategies.
Those who will succeed and thrive utilizing these programs will be the ones who blend proprietary data with curated AI applications to drive lasting differentiation.
