Melissa Gollan on Why the Future of Technology Still Needs a Human Touch

Technology often arrives with a promise of speed. A new system will automate a task, connect scattered information or shorten a process. Yet the real test begins after implementation, when a person must understand the system and depend on it.

Melissa Gollan believes technology should make that person’s life easier. Her view is direct: digital tools should reduce friction, improve efficiency and return time to people. That time can then be used for judgment, care, conversation and other distinctly human work.

This philosophy places humanity at the center of innovation. It also changes the first question behind a technology project. Instead of asking what a new tool can do, leaders should ask which meaningful problem needs to be solved.

Melissa Gollan developed that perspective through entrepreneurship. She spent eight years taking a fintech company from concept to operation, expanding its footprint across three countries. She also secured government contracts and worked on technology intended to help vulnerable community members access food and support.

Those experiences reinforced a lesson that applies well beyond one company. Innovation earns its value through the experience it creates for people. Complexity may sit behind the screen, but the result should feel clear, useful and humane.

Start With the Human Problem

New technology can create pressure to move before an organization has defined its objective. Artificial intelligence, connected infrastructure and automation may offer powerful capabilities. None of them, however, automatically identifies the right problem.

Melissa Gollan describes herself as a fixer. Persistent problems catch her attention because they signal an unmet need. Her instinct is to examine the process, understand where people struggle and consider whether technology can remove that obstacle.

That order matters. Beginning with a product can lead teams to search for places to use it. Beginning with a human problem encourages them to define the outcome first, then select the tools that fit.

The difference is visible in ordinary questions. Who is having difficulty with the current process? Which step consumes unnecessary time? What information is hard to find? What would become possible if that burden disappeared?

These questions keep innovation tied to purpose. They also help organizations avoid confusing activity with progress. A launch may be impressive, but success depends on whether the resulting system improves an experience or resolves a recurring need.

For Gollan, this is not an argument against ambitious technology. It is an argument for disciplined ambition. The possibilities may be broad, but implementation should remain anchored to people and measurable improvements in their lives.

Empathy Is a Design Requirement

Technology design is sometimes treated as a technical exercise followed by user training. Gollan’s philosophy reverses that sequence. The people affected by a system should inform how it is conceived, built and explained.

Empathy, in this context, is practical. It means understanding that users arrive with different abilities, pressures and levels of confidence. A process that appears simple to its designers may still feel confusing to someone seeking essential help.

Kindness also has an operational meaning. It can appear in plain instructions, fewer repeated questions or a clear path to human assistance. It can mean respecting a person’s time and avoiding systems that transfer administrative work onto the user.

This perspective is especially important when technology serves communities. A resident may encounter a digital service during a stressful moment. If the system assumes perfect access, technical fluency or unlimited time, efficiency for the agency can become difficult for the public.

The OECD’s principles for public service design similarly emphasize accessible, ethical and equitable services that prioritize user needs. That framework supports a central point in Gollan’s thinking: digital transformation should improve outcomes, not merely move an old process onto a screen.

Demystifying Artificial Intelligence

Gollan sees part of her evolving role as making artificial intelligence understandable to a broader community. That goal is timely because public discussion often swings between grand promises and deep anxiety. Both extremes can obscure practical questions.

Demystification begins with language. People need to know what a system is designed to do, what information it uses and where human review remains involved. Clear, concise communication helps users form realistic expectations instead of filling gaps with assumptions.

It also requires honesty about limitations. An AI-enabled tool may assist with patterns, classification or routine decisions, but it still operates within a defined context. Responsible leaders should consider error, privacy, fairness, security and the consequences of relying on an output.

The National Institute of Standards and Technology’s AI Risk Management Framework offers a voluntary structure for considering trustworthiness throughout design, development, deployment and evaluation. Its existence illustrates why useful AI conversations must include risk, accountability and human impact alongside capability.

Gollan’s emphasis is not on turning every resident or public employee into a technical specialist. It is to give people enough understanding to participate. When technology is presented in plain terms, communities can ask better questions and organizations can make more grounded choices.

Better Tools Can Return Time to People

Government agencies and community organizations often operate under pressure. Staff members manage limited budgets, complex requirements and high public expectations. Poorly connected systems can force them to repeat work instead of focusing on service.

Melissa Gollan is interested in intelligent, connected infrastructure that helps agencies align operations with legislative expectations and community needs. Her focus is not technology for its own sake. It is the possibility of creating fiscally efficient workflows that return time and resources to the people doing the work.

That time matters. A simplified process can allow an employee to address an unusual case, explain an option or speak with someone who needs help. Automation has the greatest human value when it supports those interactions instead of attempting to erase them.

This is also why efficiency should be defined carefully. Completing more transactions may be useful, but volume alone does not show whether people understood the process or received appropriate service. A faster system can still fail if it creates confusion or blocks access.

Thoughtful measurement therefore combines operational and human questions. Did the technology reduce repeated tasks? Did it shorten delays? Did staff gain capacity? Could residents complete the process, and did they know where to turn when their circumstances did not fit the standard path?

Innovation Needs Mission and Resilience

Gollan’s leadership approach reflects lessons from sports. Teams succeed by recognizing individual strengths, coordinating effort and recovering when events do not follow the plan. Innovation requires the same combination of shared purpose and resilience.

Building something new rarely follows a smooth path. Gollan has described how early setbacks once created uncertainty, while experience taught her to treat obstacles as problems that can be studied. Persistence becomes more sustainable when the mission remains meaningful.

That lesson also shapes team selection. Gollan values people who will face difficult questions rather than avoid them. Technical knowledge matters, but so do integrity, resolve and the willingness to examine whether a proposed solution truly serves its intended users.

Her advice to women entering technology follows the same practical logic. Approach the field with dedication and create something of value. If a clear opportunity exists to improve a process, trust the vision enough to investigate it and begin the work.

Measure What Became Better

Successful innovation should leave evidence beyond a launch announcement. It should solve a meaningful problem, remove a burden or create access that did not exist before. Its value should be visible in what people can now do.

This approach also changes procurement and planning. A clear problem statement gives decision makers a practical standard for comparing vendors, budgets and timelines. It helps teams distinguish necessary features from attractive extras that add cost without improving the public experience. Early conversations with staff and community members can reveal barriers that a technical specification misses. Testing with real users can then show whether instructions are understood, steps are manageable and support is available at the right moment. These practices do not eliminate every risk. They create a stronger feedback loop between the people building a system and those expected to use it every day in practice.

This standard encourages leaders to define success before choosing a tool. It may involve saved staff time, fewer incomplete applications, clearer information or improved access to support. The right measures will vary, but they should connect directly to the original human need.

It also encourages ongoing attention. People, policies and community needs change. A responsible technology program listens after launch, studies where users still struggle and improves the system rather than treating deployment as the end of the work.

For Melissa Gollan, the future of technology is not less ambitious because it needs a human touch. It is more demanding. It asks innovators to pair technical possibility with empathy, clarity and accountability.

The strongest systems may operate quietly. They remove needless steps, help organizations use resources wisely and make essential services easier to reach. Most importantly, they give people more room to exercise the judgment, kindness and connection that technology cannot replace.