Finding your AI Dynamite

Eamon Kehoe, Marketing Manager at Escher Group discusses how strong data foundations, focused experimentation, and disciplined implementation enable postal operators to safely harness AI’s transformative potential.

“It began with a bang!

In 1847, an Italian chemist named Ascanio Sobrero made a groundbreaking yet troubling discovery. An explosive substance with incredible power but equally remarkable volatility – he called the substance nitroglycerin. But despite the immense potential locked within nitroglycerin, Sobrero was alarmed by his invention, as it was dangerously unpredictable. The inherent instability of nitroglycerin led to numerous disastrous accidents, ultimately resulting in Sobrero’s invention remaining largely unused for decades.

It wasn’t until Alfred Nobel, twenty years later, discovered how to stabilise nitroglycerin by mixing it with diatomaceous earth that dynamite was born. Nobel’s invention transformed a perilously unstable explosive into a powerful yet safe tool, revolutionising construction, mining, and infrastructure development.

Today, postal operators stand at a similar crossroads when considering the adoption of Artificial Intelligence. AI offers extraordinary potential, improving operational efficiency, optimising logistics, enhancing customer experiences, and streamlining complex workflows. Yet, much like nitroglycerin, adopting AI without fully understanding its capabilities, limitations, and potential pitfalls can lead to serious complications. Hastily implemented AI systems in postal operations might result in disruptions, compromised security, financial losses, or damaged public trust.

Just as Nobel carefully harnessed the explosive potential of nitroglycerin, postal operators must take a measured and informed approach to AI adoption. Investing time and resources to thoroughly understand AI technologies, their applications, and their ethical implications is essential. By doing so, postal operators can transform AI from a risky gamble into a safe, reliable tool that drives meaningful innovation and sustainable growth.

AI isn’t inherently safe or dangerous. It becomes one or the other based on how it’s adopted.

Unstable Explosive or Powerful Tool?

Artificial Intelligence, like early nitroglycerin, holds vast potential, but only if handled with care. Postal operators face a clear paradox: AI promises significant gains in efficiency and customer service, yet rushed or uninformed implementation can lead to costly failures.

Research shows that premature AI adoption, without proper data, testing, or safeguards, often backfires.

Many operators overestimate AI’s abilities, expecting flawless results without the groundwork. But AI thrives only on quality data and careful deployment. Skipping these steps invites instability, much like Sobrero’s volatile invention before Nobel refined it.

But instability isn’t destiny. Operators who have built their AI initiatives gradually, with strong data practices, workforce training, and deliberate testing, are now seeing tangible returns: better efficiency, lower costs, and happier customers.

AI isn’t inherently safe or dangerous. It becomes one or the other based on how it’s adopted. The first step toward unlocking its potential is understanding that critical distinction and acting accordingly.

Lighting the Fuse – High-Impact AI Applications in Postal Operations

Just as dynamite reshaped entire industries through its controlled power, carefully deployed Artificial Intelligence is beginning to reshape postal operations worldwide profoundly. From customer service to logistics and sorting, AI drives tangible improvements in efficiency, accuracy, and customer satisfaction.

Enhancing Customer Experience with Intelligent Automation

AI-powered chatbots are redefining customer service. These tools handle routine inquiries, such as tracking, pricing, and service availability, freeing staff to manage more complex issues. Lithuania’s postal service, for instance, introduced “Mantas,” a chatbot that now handles up to 500 daily questions. Results include faster response times, reduced staff workload, and up to 50% shorter wait times with a 30% increase in first-contact resolution.

Precision in Logistics and Route Optimisation

AI’s predictive algorithms enhance logistics by forecasting demand, managing inventory, and adjusting delivery routes in real time. This leads to fuel savings, lower labour costs, and improved reliability. For example, some operators now reroute parcels ahead of storms, minimizing disruptions before they occur. Route optimisation alone has improved operational efficiency by as much as 20% and cut fleet maintenance costs.

Accelerating Accuracy in Sorting and Processing

Sorting centres are also seeing AI’s impact. Technologies like computer vision and OCR now interpret handwriting and complex addresses faster and more accurately than traditional systems. In the U.S., processing speed was increased tenfold after adopting AI, leading to faster delivery with fewer errors.

Across functions, AI proves its value when implemented strategically, streamlining tasks, improving accuracy, and freeing human workers for higher-value work. These early deployments show that with the right use, AI is more than a trend; it’s a catalyst for lasting, meaningful change.

Consistently, here some of things you likely to find in successful AI implementations:

1. Clearly defined use cases – Interacting with an LLM model is like interacting with your engineers (be direct and specific)
2. Start with small experiments – 50% of your AI investments will fail, but you will not know which 50% until you try, so start with small experiments and grow them from there
3. Data is critical – Like most Operations investments, data is critical to success. Clean data, consistent attribution, and history, combined with clearly defined use cases, will lead to success
4. Create your own benchmarks – Most of the benchmarks you read about were created by firms trying to sell you AI “services,” chips, infrastructure etc. Listen to them at your own peril.  Focus on your data and your use cases.
5. Specificity, not generality – General LLMs struggle in operations because they lack industry-specific knowledge. While they can handle broad tasks like writing a printer driver, most industries have unique processes, regulations, and histories. Trusting them with critical operations requires significant training on your data and overcoming habits from their general-purpose design.

 Safely Handling Your AI Dynamite – Key Implementation Considerations

Harnessing AI’s potential requires the same precision that Nobel used to stabilise nitroglycerin. Without careful planning, even the most promising tools can cause disruption. For postal operators, success starts with four essential pillars:

1. Prioritise Data Quality. AI thrives on accurate, comprehensive data—but postal systems often deal with fragmented, inconsistent datasets. Before deploying AI, successful operators audit their data, unify databases, and improve collection practices. Clean, well-organized data dramatically boosts AI performance and reliability.
2. Integrate Thoughtfully with Legacy Systems. Many postal operators rely on decades-old infrastructure, making integration complex. A phased approach—starting with pilot projects—helps identify technical hurdles early. Using API-based tools and prioritizing interoperability simplifies the transition and reduces costly missteps.
3. Train Your Workforce. AI changes how people work. Without training, staff may resist or misuse new systems. Investing in AI literacy across an organization by providing specialized training for key roles emphasizes collaboration over replacement, building trust and acceptance, ultimately, making the transition to augmented AI workflows smoother.
4. Ensure Data Security and Privacy. Postal operators manage vast amounts of sensitive information. Mishandling that data—especially with AI systems—can erode trust and invite legal trouble. Proactive operators set clear internal policies, choose secure tech partners, and communicate transparently with customers about how data is used.

Controlled Explosions – Successfully Managing AI Deployment

Alfred Nobel didn’t tame nitroglycerin overnight—and postal operators shouldn’t rush AI deployment either. Success depends on a disciplined, strategic rollout to harness its power safely. These proven approaches guide that process:

AI doesn’t’ require a full-scale overhaul. Leading operators begin with targeted pilots—chatbots in customer service or automated sorting in select centres—gathering feedback and refining as they go. Each phase provides insights, reduces risk, and builds confidence among staff and stakeholders.

Not every organisation has deep AI expertise. By collaborating with technology providers, cloud services, or AI startups, postal operators access advanced tools and skills without heavy upfront investment. These partnerships accelerate timelines and reduce internal development burdens.

External help is valuable, but lasting success requires internal strength. Forward-thinking operators train AI specialists, appoint project leads, and create innovation hubs or centers of excellence. Building in-house expertise ensures AI becomes a long-term capability, not a one-off project.

AI flourishes in a culture that welcomes change. Organisations that involve employees at all levels, encourage experimentation, and reward feedback tend to see greater adoption success. When people feel part of the process, AI becomes an enabler rather than a threat.

 Measuring the Blast Radius – Evaluating AI Success

Nobel’s dynamite changed the world not just through power, but through precision. Likewise, delivery companies must measure AI’s impact to guide future investments and refine strategy. Tracking the “blast radius” means using clear, meaningful metrics.

Operational Efficiency

AI-driven tools often deliver dramatic gains. Optical character recognition has accelerated sorting by up to 10x, while predictive maintenance has cut unplanned equipment downtime by 50%. These improvements translate directly into faster service, fewer errors, and lower costs.

Cost Savings and Revenue Growth

AI reduces expenses in customer service, logistics, and fleet management. Route optimisation, for instance, has led to 5–10% savings in fuel and labour costs. At the same time, AI enables revenue generation, like personalized product offers at postal counters or online, mirroring retail strategies that have boosted revenue by up to 35%.

Customer Experience

AI improves responsiveness, reduces delays, and enhances communication. Chatbots have halved wait times and increased first-contact resolution by 30%. Some operators report fewer customer complaints and higher satisfaction ratings—clear indicators that AI is improving service quality and trust.

Employee Productivity and Satisfaction

Beyond automation, AI frees employees from repetitive tasks, letting them focus on meaningful work. Tracking changes in job satisfaction, engagement, and productivity helps operators assess AI’s broader impact, not just on workflows, but on morale and retention.

AI, thoughtfully integrated, becomes a catalyst for remarkable innovation.

Harnessing AI for Sustainable Growth

Alfred Nobel’s breakthrough didn’t just unleash power; it reshaped entire industries. Today, postal operators face a similar opportunity with Artificial Intelligence.

The path to success is clear: understand AI’s capabilities and risks, proceed with strategy and care, and focus on sustainable integration. Like dynamite, AI must be stabilised before it can safely deliver transformative results.

This transformation isn’t about adopting technology for its own sake; it’s about unlocking long-term value. Operators who take time to manage data, modernise systems, train employees, and build strong partnerships consistently outperform those who rush. These deliberate efforts result in more than operational gains, they open the door to new services, stronger customer relationships, and lasting competitive advantage.

The real-world evidence underscores a clear truth. AI, thoughtfully integrated, becomes a catalyst for remarkable innovation. With strategic planning around data management, legacy system integration, workforce training, security, and collaborative partnerships, postal operators can turn the volatility of AI into a controlled, powerful force for change.”

Some practical next steps.

• Evaluate Your Readiness: Conduct an AI-readiness audit, examining current capabilities, data quality, and existing systems.

• Pilot Strategic Initiatives: Launch targeted pilot projects in high-impact areas, like customer service or sorting operations, to validate AI’s potential and gather early learnings.

• Build Internal Expertise: Invest in workforce training and begin building internal AI capabilities. Provide tailored, role-specific AI literacy programs to empower your employees.

• Establish Strategic Partnerships: Collaborate with proven technology experts and solution providers who understand the unique needs of postal operations.

• Measure Early and Often: Clearly define metrics for success early on, tracking operational efficiency, cost savings, customer satisfaction, and employee engagement meticulously.