Mojeed Abisiga: Fostering Innovation, Advancement and Professional Development of Global Data, AI Community

Mojeed Abisiga is an award-winning Data & AI Leader, entrepreneur, technology educator, public speaker, and Forbes Technology Council member, recognised as a Marquis Who’s Who Honoree, an Einstein Visa Green Card recipient. He is the CEO & Founder of AI Every Time, the world’s first 24/7 AI newsroom and AI content hub where people can follow, chat with, and learn directly from AI reporters & AI learning companions around the globe, each bringing a unique identity, expertise, and cultural voice, and the Founder & CEO of DataGlobal Hub, a platform dedicated to being a one-stop platform for news, education, networking, and professional opportunities in data science and AI. By fostering innovation, knowledge sharing, and collaboration, he promotes the advancement and professional development of the global data and AI community. In this interview, Mojeed, who is passionate about helping individuals and organisations understand, adopt, and leverage AI, shares how to create new opportunities and shape the future of work and technology. Precious Ugwuzor brings excerpts

You are an award-winning Data & AI Leader, entrepreneur, educator and public speaker. What sparked your journey into the world of data and artificial intelligence?

My journey began with a fascination for numbers and a belief that an insight can be more valuable than a billion data points. Winning a national climate-change competition and joining a UNESCO-sponsored research tour showed me early that data-driven insights can shape policy and improve real lives. Mathematics gave me the foundation, consulting and machine-learning work gave me practical discipline, and education gave me purpose. The thread connecting everything has been the desire to turn complexity into something people can understand and use; AI is the most powerful extension of that mission I have encountered.

You founded AI Every Time, described as the world’s first 24/7 AI newsroom and AI content hub. What inspired this groundbreaking concept?

The inspiration was the gap between content reach and human attention: a creator or educator on AI can reach millions of people, but cannot answer millions of follow-up questions, remember every learner, or remain available at 2 a.m. Here is where AI Every Time comes in, The World of AI taught by your local AI voices that never sleep. Chat and learn about AI from your local AI voices now. AI Every Time turns a piece of content into the beginning of a relationship rather than the end of a view. We are building the world’s first 24/7 AI newsroom and AI learning hub where people can follow, chat with, and learn about AI directly from AI reporters/learning companions around the globe, each representing different countries, bringing a unique identity, expertise, and cultural voice. The purpose is not to remove human expertise; it is to make trusted knowledge more accessible, responsive, and useful at global scale. Video ends → learning begins.

How is AI Every Time redefining the way people consume news, learn and interact with information?

Our platform delivers always-on Al news and education through local Al voices that writes content, explain it, answer questions, and personalize learning for users in real time. It transforms learning of AI from passive content consumption into interactive conversations, making creators accessible to their audience at all times. We also solve one of the biggest issues with AI content, which is that it often sounds robotic or obviously AI-generated. Our platform creates learning experiences that feel human, clear, and engaging. Learn from your local AI voices that never sleep. Chat, learn, and stay updated in a personalized and interactive way with our AI learning companions.

You are also the Founder and CEO of DataGlobal Hub. What gap in the global data and AI ecosystem are you seeking to address?

The ecosystem is rich in talent and information but fragmented across countries, platforms, events, courses, jobs, and professional communities. DataGlobal Hub was created to bring those pieces together and make high-quality data and AI knowledge, opportunities, and networks easier to access, especially for people who are outside the traditional centers of technology. The vision is to build a trusted global destination for learning, news, community, and professional growth in the data and AI field. AI Every Time advances that mission by moving from publishing knowledge to making knowledge available as a continuous conversation.

Artificial intelligence is transforming virtually every industry. Which sectors do you believe will experience the most dramatic disruption in the next five years?

The fastest disruption will occur where work is information-intensive, repetitive, and digital: media, education, software development, customer service, finance, marketing, legal services, and professional services. Healthcare, manufacturing, agriculture, telecommunications, and government will also change significantly, but adoption there will depend more heavily on safety, infrastructure, regulation, and trusted human oversight. The important distinction is that AI will not transform every sector in the same way: in some places it will automate production, in others it will augment decisions, and in the most consequential settings it must remain a tool under accountable professional judgment.

What does the rapid advancement of AI mean for the future of jobs, particularly for young people entering the workforce?

AI will change tasks before it eliminates entire professions, but young people are exposed because many entry-level jobs are built around the routine research, drafting, analysis, and coordination that AI can now perform. The opportunity is to move up the value chain earlier: learn to define the problem, direct AI, verify its output, communicate with people, and take responsibility for the result. PwC reports that employer skill requirements are changing 66 percent faster in AI-exposed occupations, which means the real career risk is not AI itself; it is standing still while the work changes around you.

Should workers be afraid that AI will replace their jobs, or should they see it as an opportunity to become more productive and competitive?

Workers should take the disruption seriously without surrendering to fear. Some tasks and roles will disappear, and the transition will not be painless, but the evidence also shows strong productivity and wage gains where workers develop valuable AI skills. PwC found that industries most exposed to AI achieved three times higher growth in revenue per employee than the least-exposed industries, while job numbers were still growing in virtually every AI-exposed occupational category studied. The practical response is to treat AI as a colleague that needs direction and supervision: automate the routine, strengthen your judgment, and keep learning.

** Nigeria has a large young population and growing technology ecosystem. What opportunities does AI present for Nigeria and Africa?**

AI gives Nigeria and Africa an opportunity to leapfrog constraints in education, healthcare, agriculture, finance, public services, and access to expertise. The biggest prize is not simply importing global tools; it is building systems around African languages, cultures, markets, and problems. McKinsey estimates that at-scale generative AI deployment could unlock between $61 billion and $103 billion in additional annual economic value across Africa. If we combine our young talent, entrepreneurial energy, and local knowledge with better infrastructure and responsible governance, Africa can become a producer of AI solutions rather than only a consumer of them.

What are the biggest barriers preventing Africa from becoming a major global player in artificial intelligence?

The barriers form a connected system: limited and expensive compute; unreliable power and connectivity; insufficient high-quality local data; shortages in advanced skills and research capacity; limited capital for scaling; fragmented policy; and low public trust. Africa also needs models that understand local languages and can work in low-connectivity settings. The answer is therefore bigger than training more data scientists: governments and industry must build digital public infrastructure, interoperable data systems, regional compute capacity, responsible regulation, and pathways that help local research and startups reach the market.

As a technology educator, what are the most important AI skills young Africans should begin developing today?

Young Africans should build three layers of capability. The first is technical literacy: data, prompting, automation, coding, and an understanding of how models work and fail. The second is judgment: critical thinking, source verification, ethics, privacy, and the ability to test an answer rather than admire it. The third is human value: communication, creativity, domain expertise, collaboration, and entrepreneurship. Tools will change quickly, so the most durable skill is learning how to learn. Do not compete with AI at producing generic answers; become excellent at asking better questions and applying answers to real African problems.

** You have been recognized by the Forbes Technology Council and Marquis Who’s Who. How have these recognitions influenced your professional journey and global outlook?**

My membership in Forbes Technology Council and my inclusion in Marquis Who’s Who have expanded my exposure to different markets, leadership perspectives, and standards of execution. I value these recognitions as professional milestones, not as endorsements of every view I hold or every organization I build. They increase my responsibility to contribute thoughtfully, represent African innovation with integrity, open doors for others, and use a wider network to make data and AI knowledge more accessible. I am speaking here in my personal capacity, and my views do not represent Forbes or Forbes Technology Council.

The Internet Is No Longer Human: Who Will Teach Us What to Believe?” Is this the defining question of the AI era?

Yes, because the internet is changing from a network where humans create most content into one where machines can generate, personalize, and distribute information at enormous scale. That makes platforms such as AI Every Time more important because people need always-available, local, conversational help to understand AI and ask better questions. The answer is not for one company, government, journalist, or AI system to dictate belief; it is to give people accessible explanations, visible sources, multiple perspectives, and the confidence to exercise judgment. The scarce resource is no longer information; it is trusted understanding.

** With AI now capable of generating realistic text, images, audio and video, how can society distinguish truth from sophisticated misinformation?**

We need to stop relying only on our eyes and ears and start using a disciplined verification routine: identify the original source, inspect the evidence, compare independent credible outlets, check the date and context, and pause before sharing emotionally charged content. Technical provenance such as Content Credentials can act like a nutrition label by recording where media came from and how it was edited, but the supporting cybersecurity guidance is clear that provenance indicates authenticity context, not whether a claim is true. This is why an AI newsroom should make sources, context, correction, and clear AI identity visible. The solution combines responsible AI reporting, provenance, detection, professional verification, platform accountability, and public media literacy.

If machines increasingly create the information we consume, who should we trust to determine what is factual?

We should place confidence in a transparent process rather than depend blindly on a single authority. For important claims, that process should show the primary evidence, disclose who produced or funded the information, separate fact from analysis, compare independent sources, reveal material uncertainty, and provide a correction mechanism. Journalists, scientists, public institutions, technology platforms, and AI systems all contribute to that process. AI Every Time can earn its place within it by making information easier to question, explain, source, and correct, helping users reach informed conclusions rather than asking them for blind belief.

Could AI-powered personalization and algorithms eventually become powerful enough to manipulate public opinion and human behaviour?

They are already powerful enough to shape attention, and influence begins with deciding what people repeatedly see, what is hidden, and what is framed as normal. Generative AI raises the stakes because persuasion can be personalized, tested, and delivered at scale. The answer is not to reject personalization; it is to use personalization in service of goals the user understands and chooses. People should be able to see why they received a recommendation, whether it was sponsored, what data influenced it, and whether they are interacting with a human or an AI agent. For AI Every Time, personalization should deepen learning and relevance, never quietly manipulate belief.

What happens to journalism when AI can produce news stories, conduct research and deliver information 24/7?

Journalism becomes faster, more continuous, multilingual, personalized, and conversational. AI can monitor developments, summarize documents, translate reporting, explain complex topics, and answer follow-up questions 24/7. AI Every Time is built for that always-on explanatory layer. Trust is earned by clearly identifying AI reporters, making sources and uncertainty visible, providing correction pathways, and applying appropriate human editorial oversight to sensitive or consequential claims. Audience skepticism is real: the 2024 Reuters Institute research found that 52 percent of US respondents and 63 percent of UK respondents were uncomfortable with news produced mostly by AI, so transparency is not a limitation on an AI newsroom; it is its competitive advantage.

Do you believe AI will strengthen human creativity, or could excessive dependence on machines gradually weaken our ability to think independently?

Both outcomes are possible. AI can help people explore more ideas, cross language barriers, prototype quickly, and create in forms that previously required expensive tools or specialist skills. But if we accept the first generated answer, allow AI to replace struggle, or stop forming our own point of view, convenience can become intellectual dependency. The discipline is to use AI as a sparring partner rather than an oracle: ask it for alternatives, challenge its assumptions, verify its evidence, and then make the final creative decision yourself. AI should expand the imagination, not occupy it.

What ethical safeguards should governments, technology companies and AI developers put in place to ensure that AI remains beneficial to humanity?

The safeguards should follow the lifecycle of an AI system: clear responsibility for high-stakes decisions; privacy and data minimization; rigorous testing for safety and bias; disclosure when people are interacting with AI; traceability of synthetic media; security against misuse; independent audits; user control; and accessible redress when harm occurs. These safeguards are not anti-innovation; they are trust infrastructure that helps responsible AI platforms grow. Governments should protect rights and set risk thresholds, companies should build transparency and accountability into products, and educators and media should strengthen public literacy. UNESCO’s guidance adds a vital principle: AI in education should remain human-centered, age-appropriate, equitable, and designed to preserve agency.

Looking ahead, what will the internet look like when humans and AI agents are both major creators, publishers and consumers of information?

The internet will become more agentic: AI systems will not only answer questions but also create, recommend, negotiate, purchase, and act for people and organizations. Information may increasingly be produced for machines to read and other machines to act upon before a human sees it. That makes identity, authorization, provenance, audit logs, limits, and recourse essential infrastructure. The best version of this future is not an internet without humans; it is an internet in which AI handles scale and complexity while people retain agency, cultural plurality, moral responsibility, and the right to understand and challenge consequential decisions.

If you could leave governments, business leaders, educators and the next generation with one message about AI and the future of humanity, what would it be?

Use AI boldly to expand access, understanding, creativity, and opportunity, but do not surrender belief, judgment, or responsibility to any machine or institution. Governments should build rights and trust into the infrastructure; businesses should use AI to create value; educators should teach students how to question and verify; and the next generation should learn to direct AI confidently. My optimism comes from the conviction behind AI Every Time: AI can democratize knowledge and multiply human capability when it is local, conversational, personalized, transparent, and designed to help people choose their own future.