Automation: The Silent Partner in AI’s Success
Artificial Intelligence (AI) has become the star of every boardroom conversation, marketing pitch, and tech panel. It’s the term that sparks curiosity, signals innovation, and suggests the future is here. Yet, as AI captures the spotlight, its no-less-impressive counterpart—automation—often gets relegated to the shadows. The problem? As businesses and consumers alike grapple with understanding the capabilities of these technologies, the conflation of the two threatens to dilute the true promise of either of these tools.
Thorsten Brueckner, Senior Data Scientist at Locaria, is here to shed some light on this distinction. Automation, he explains, is the foundation of modern technology ecosystems. Far from being static or pedestrian, it drives seamless workflows, reduces human error, and scales efficiencies in ways previously unimaginable. At its core, automation is powered by predefined rules: “If this, then do that.” It executes repetitive tasks, enforces consistency, and enhances productivity—all without fanfare. Yet, it does not adapt or evolve on its own. When refinements are needed, the rules must be updated by human intervention.
In contrast, AI thrives in complexity and unpredictability. Brueckner describes it as dynamic intelligence—a system capable of learning, adapting, and improving without constant human oversight. Through iterative feedback loops, AI refines its processes, evolving in ways that automation alone cannot. This capacity for self-improvement and problem-solving underpins AI’s allure. Intelligence, in this sense, is synonymous with adaptability and growth.
Yet, the distinction between AI and automation is often muddied, particularly in the marketplace. The root of the problem lies in the incentives facing tech companies. In an era where the allure of AI commands investor attention and consumer intrigue, many automation tools are being rebranded as AI. “If all your competitors offer fancy AI solutions and you don’t, you either make a really strong case for why you don’t, or you follow suit and rebrand your offering,” Brueckner notes. The result? A landscape where tools built on decades-old statistical algorithms are being marketed as cutting-edge AI, despite lacking the hallmarks of true intelligence.
The Costs of Mislabeling
This trend is more than just semantic sleight of hand; it carries tangible risks. For one, it inflates expectations around AI’s capabilities. Companies that invest in tools marketed as AI but driven by simple automation may find themselves disappointed, their faith in the technology eroded. Moreover, this mislabeling obfuscates the genuine advances being made in AI, overshadowing groundbreaking developments with noise from opportunistic rebranding.
Brueckner points out that true AI—the kind that learns and adapts—is a costly and resource-intensive endeavor. Training a self-learning AI model requires vast datasets, robust computational power, and complex feedback loops to refine its outputs over time. Few tools on the market today meet these stringent criteria. Instead, “80% of what’s branded as AI is likely automation,” he estimates, with only a fraction of tools offering genuine intelligence. Even among those, many use cases would be better served by simpler, more cost-effective automation solutions.
Automation’s perceived inferiority stems, in part, from its branding problem. As Brueckner quips, “Automation is the ugly duckling, even though it potentially outperforms AI in many ways.” The reality is that automation powers much of today’s technological infrastructure, from customer service chatbots to supply chain management systems. Its reliability, efficiency, and scalability make it indispensable. Yet, because it lacks the mystique of AI, it is often overlooked or repackaged to fit the AI narrative.
When to Use AI, and When to Stick with Automation
The mischaracterisation of automation as outdated or inferior belies its transformative potential. Far from being a relic of the past, automation powers much of the digital world. From streamlining global marketing campaigns to managing multilingual workflows, automation is the silent workhorse behind countless innovations.
At Locaria, proprietary automation tools are the cornerstone of the agency’s efficiency and precision in multilingual content adaptation and management. These tools are anything but simplistic. They are meticulously designed to handle the complexities of modern global marketing, delivering results with speed, consistency, and scale. Brueckner emphasises that automation’s strength lies in its reliability and elegance. It is not a stopgap for AI but a technology that shines in its own right.
Automation tools by Locaria:
LEXICLAVIA: LEXICLAVIA is an advanced keyword research tool developed to automate and enhance the keyword discovery process. It offers a significant upgrade over Google Keyword Planner, enabling the generation of up to 10,000 new keyword ideas at once with DeepL-integrated backtranslations, and LLM support for multilingual keyword variations.
K-ATTUNE: K-ATTUNE resolves keyword cannibalisation issues across Organic and PPC, ensuring clear prioritisation, improved targeting, and optimised search performance. K-ATTUNE helps streamline content strategies, enhance efficiency, and unlock optimised search performance.
“Automation may lack the buzzword appeal, but it delivers results that speak for themselves,” Brueckner asserts. Whether it’s powering localised content at scale or optimising complex workflows, automation is indispensable to the future of global business.
The Way Forward
The tendency to overstate AI’s ubiquity has implications for how we perceive technological progress. Brueckner’s observations from the Web Summit 2024 underscore this concern. While there are genuine advances—such as generative AI tools and sophisticated language models—many touted “AI” innovations are little more than rebranded automation. This rebranding, while commercially expedient, risks overshadowing the real breakthroughs that could reshape industries.
As businesses navigate the hype, a more nuanced understanding of AI and automation will be critical. Automation is not a relic of the past; it remains a powerful tool for efficiency and precision. At the same time, AI’s transformative potential should not be understated—but nor should it be overstated. Recognising when to deploy each technology—and being transparent about their respective roles—will be essential for fostering trust and delivering real value in the age of intelligent systems.
Insights from: Thorsten Brueckner, Senior Data Scientist
Written by: Oliver Barham, Global Marketing Manager
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