While AI may be transforming how agencies work, technology alone is not enough to drive meaningful change. Lasting adoption depends on leadership, trust, and a clear understanding of where human judgment still matters.
To learn more, we recently caught up with MediaOne Chief Operating Officer June Goh.
June discusses the leadership required to integrate AI successfully, the skills marketers will need as the technology becomes more deeply embedded in agency operations, and why trust, governance, accountability, and human judgment will remain essential. She also reflects on receiving a Gold Stevie Award for Women in AI Leadership at this year’s Asia-Pacific Stevie Awards.
As AI takes on more analytical and operational work, what qualities will distinguish the most effective leaders?
The strongest leaders will be those who can combine technological understanding with sound human judgment.
Leaders do not need to know how to build every AI model, but they must understand what the technology can do, where it may fail, and how it should be incorporated into real business processes. They must also be able to ask the right questions instead of simply accepting an AI-generated recommendation.
Clarity will become especially important. Employees need to understand why AI is being introduced, how it will affect their work and what remains their responsibility. Without that clarity, even a good technology implementation can create fear or resistance.
Empathy, adaptability and accountability will also distinguish effective leaders. AI transformation is ultimately a change-management exercise. Leaders must listen to their teams, provide appropriate training and create an environment where people can experiment without feeling that every mistake will be punished.
Leaders do not need to know how to build every AI model, but they must understand what the technology can do, where it may fail, and how it should be incorporated into real business processes.
Most importantly, leaders must remain accountable for decisions. Technology may provide the analysis, but leadership still means taking responsibility for the outcome.
You have spoken about AI as something that should complement rather than replace people. Where do you believe human judgment will remain indispensable in marketing?
Human judgment will remain indispensable wherever context, empathy, ethics and commercial trade-offs are involved.
AI can identify patterns and recommend possible actions, but it does not fully understand the history of a client relationship, the sensitivities surrounding a brand or the internal realities affecting a business decision. A technically correct recommendation may still be commercially inappropriate or poorly timed.
Marketing also involves understanding motivations that are not always visible in the data. Customers may say one thing but feel another. A strategist must interpret cultural nuances, organisational priorities and emotional responses that an AI system may overlook.
AI can produce many ideas very quickly, but people must decide which ideas are distinctive, relevant and worth pursuing.
Creativity is another area where human direction remains essential. AI can produce many ideas very quickly, but people must decide which ideas are distinctive, relevant and worth pursuing. Without human direction, AI-generated content can easily become generic.
Finally, judgment is critical when marketing decisions have ethical, reputational or social consequences. AI can support the decision, but people must determine whether it is responsible, fair and aligned with the organisation’s values.
MediaOne has integrated Digimetrics.ai across SEO, paid media, content, reporting and campaign optimisation. Where has it made the greatest impact?
The greatest impact has been in the quality and speed of decision-making.
Digital marketing teams are surrounded by data, but having more data does not automatically lead to better decisions. Before Digimetrics.ai, strategists could spend several days compiling competitor information, reviewing keyword gaps, checking campaign performance and preparing reports. The platform can now perform much of that analysis within minutes, helping our teams identify issues and opportunities earlier.
However, the real value is not simply that tasks are completed faster. Digimetrics.ai gives our strategists a more structured way to prioritise their work. It helps them understand which opportunities are likely to produce the greatest impact, where media budgets may be wasted and which competitor movements deserve attention.
This allows our people to spend less time collecting and organising information, and more time interpreting it, developing strategies and advising clients. That shift from manual reporting to higher-value thinking has been the most important transformation for us.
As agencies integrate AI more deeply into their operations, how should they approach trust, governance and accountability?
Trust cannot be added after an AI system has already been deployed. It must be designed into the process from the beginning.
Agencies should first establish clear rules covering how client data may be used, which information may be entered into external systems and which outputs require human review. Employees should know where the boundaries are rather than being expected to make individual guesses.
There should also be clear ownership. Every important AI-assisted output should have a person who is responsible for checking its accuracy, relevance and potential risks. Saying that “the AI produced it” cannot become an excuse for an incorrect recommendation or misleading claim.
Trust cannot be added after an AI system has already been deployed. It must be designed into the process from the beginning.
Transparency is equally important. Agencies should be able to explain, in practical terms, how AI contributed to an analysis or piece of work. This does not require revealing every technical detail, but clients should understand the role the system played and the safeguards that were applied.
At MediaOne, our approach has been to combine governance guidelines covering data use, transparency and bias with human accountability for final decisions.
What are the most significant barriers agencies face in adopting AI and driving technological transformation, and what advice would you offer for overcoming them?
One major barrier is starting with the technology rather than the business problem. Agencies sometimes purchase several AI tools without first identifying the workflows they are trying to improve. This creates more complexity instead of reducing it.
Another challenge is fragmented data. When information is spread across advertising platforms, analytics systems, spreadsheets, project management tools and individual employees, AI cannot produce consistently useful recommendations.
AI transformation should not be treated as a one-off software implementation. It is an operating-model change that requires continued refinement.
There is also a people barrier. Employees may fear that AI is being introduced to reduce headcount, while managers may expect adoption without providing sufficient training or guidance. This creates passive resistance.
My advice is to begin with a small number of measurable use cases. Select repetitive or data-heavy processes where the impact can be clearly demonstrated. Involve the employees who actually perform the work, document the new workflow and decide how success will be measured.
Agencies should then invest in training, data quality and governance before scaling. AI transformation should not be treated as a one-off software implementation. It is an operating-model change that requires continued refinement.
The World Economic Forum’s Future of Jobs Report 2025 found that human skills such as communication, creativity and adaptability are becoming more valuable alongside AI. Which skills will set the strongest marketers apart?
I believe the strongest marketers will combine AI fluency with five important human capabilities.
The first is analytical thinking. Marketers must be able to interpret information, challenge assumptions and distinguish a meaningful insight from an interesting data point.
The second is communication. A strong marketer must explain complex ideas clearly to clients, management and colleagues who may not share the same technical background.
The third is creativity. As AI makes content production easier, original thinking and the ability to find a compelling angle will become more valuable, not less.
The fourth is adaptability. Platforms, consumer behaviour and search technologies are changing quickly. Marketers must be prepared to learn continuously and revise their methods.
Finally, curiosity will be a major differentiator. The best marketers will not only ask AI for an answer. They will ask why the answer matters, what may be missing and what other possibilities should be explored.
The World Economic Forum similarly identifies analytical thinking, creative thinking, resilience, technological literacy and curiosity as increasingly important capabilities.
What advice would you give students entering university today as they prepare for careers likely to be transformed by AI?
Do not prepare for a single job title. Prepare yourself to keep learning for jobs that require a set of skills that combine human EQ and technological IQ.
Many of the tasks associated with today’s entry-level jobs will change, but this does not mean young people will have fewer opportunities. It means they must learn how to work with technology and demonstrate value beyond completing routine tasks.
Students should develop basic AI literacy regardless of their field of study. Learn how AI systems work, how to use them productively and how to recognise when their outputs may be unreliable. At the same time, build genuine expertise in a domain such as marketing, finance, design, healthcare or engineering. AI becomes much more valuable when it is guided by someone who understands the subject.
Communication, critical thinking, teamwork and adaptability should not be treated as secondary skills. They will determine whether someone can turn technical capabilities into meaningful results.
I would also encourage students to build things. Complete internships, develop projects, solve real problems and create a portfolio that demonstrates how you think. Qualifications may open the first door, but curiosity, initiative and the ability to apply what you have learned will shape your career.
You received a Gold Stevie for Women in AI Leadership at this year’s Asia-Pacific Stevie Awards. Can you tell us more about the recognition and what it means to you personally?
Receiving the Gold Stevie for Women in AI Leadership was deeply meaningful because it recognised not just the technology we have built, but the work involved in making AI useful to people.
At MediaOne, my role has been to turn AI from an interesting technical concept into something our teams can confidently use in their everyday work. This has involved redesigning workflows, introducing governance guidelines, supporting staff adoption and ensuring that our AI initiatives contribute to better client and business outcomes.
The recognition was also personally significant because I hope it encourages more women to see themselves as AI leaders. You do not necessarily need to be a software engineer or data scientist to lead an AI transformation. Leadership also requires understanding people, identifying operational problems, managing change and helping teams use technology responsibly.
The award followed MediaOne’s two Gold Stevie wins in 2025 for its work in artificial intelligence, machine learning and paid media management, so I see it as recognition of a sustained organisational effort rather than an individual achievement alone.
Quick Hits
A useful app or tool you have started using recently:
Google NotebookLM. I find it useful for bringing together source materials, reviewing lengthy documents and identifying connections across different pieces of information. Within MediaOne, I naturally also use Digimetrics.ai extensively to support our marketing and operational decisions.
Book, podcast or resource you recommend:
It’s definitely “Co-Intelligence: Living and Working with AI” by Ethan Mollick. It provides a practical and accessible way of thinking about how people can work with AI, rather than viewing it only as a technology that will replace jobs.
Something you want to learn or get better at:
Designing and applying agentic AI systems that can independently plan, make decisions and complete complex workflows. I believe agentic AI will fundamentally reshape how organisations operate, and understanding how to deploy it responsibly will be essential to improving productivity without losing human judgment, accountability and trust.
