As artificial intelligence rapidly evolves from an experimental novelty to an essential business utility, enterprises across Australia and New Zealand face an inflection point that extends far beyond the technologies themselves. At the heart of this transition is a pressing question: can organizational readiness—in terms of people, processes, and ethical frameworks—keep pace with the dazzling speed of AI adoption?
In the corridors of enterprise IT and business strategy, this moment feels hauntingly familiar to cybersecurity’s boom years. Michael Blignaut, IT and process instructor at Lumify Work New Zealand (formerly Auldhouse, with DDLS in Australia), sounds the alarm: “Cybersecurity is our fastest growing area,” he states, noting an identical sense of urgency now gripping AI advancement. “Every single one of our partners—AWS, Microsoft, all of them—have got huge amounts of cybersecurity training.” That same energy is now being funneled into AI, with organizations scrambling to educate people even as they integrate AI tools into everyday operations.
Lumify, Australasia’s largest corporate IT training provider, has nearly four decades of perspective on workplace upskilling in IT, project management, cybersecurity, and more recently, an expanding suite of AI-focused courses. It’s a vantage point that exposes a recurring challenge: the assumption that technological sophistication is synonymous with organizational readiness.
But behind the excitement lurk new risks. Many users either mistrust the tools—often due to “wrong answers”—or, conversely, swallow the output whole, risking overreliance. As Blignaut points out, “There’s also an overreliance: everything from ‘it can solve all our problems’ to ‘it’s not doing what I need.’” His comments echo findings from global research firms, such as Gartner and IDC, which have warned of gaps in AI literacy and the hazards of automation when humans disengage from critical review.
This raises a crucial point: successful AI adoption is not merely about access to new tools, but about internal frameworks that anticipate misuse, bias, regulatory pitfalls, and workforce displacement. Lumify’s advice begins with assessment—utilizing AI readiness evaluations to determine where organizations really stand and what risks they must address before rollout.
For enterprise leaders, Blignaut urges, “It’s about thinking through your adoption strategies—and not being slow about putting in place really great implementation pathways.” This means clarifying who will use these tools, for what purposes, and under what safeguards.
This diversification is critical. While vendor certifications from giants like Microsoft or Amazon retain their value, organizations increasingly demand vendor-neutral, tool-agnostic programs. AI Certs, an internationally recognized certification body, has surged in prominence—offering credentials that outlast any single platform’s life cycle and adapt rapidly to change. Blignaut notes, “Keeping certifications current and standard is going to be a huge amount of work for them, but so far, so good.”
This notion is strongly supported by research. Misuse and misunderstanding of AI systems frequently trace back to poorly framed instructions or over-generalized queries. The emerging discipline of “prompt engineering” is now recognized as essential, with firms investing heavily in both technical and non-technical staff to learn this art.
Equally vital are critical thinking and iterative refinement. “AI does hallucinate,” Blignaut warns, echoing widespread reports of generative models providing plausible-sounding—but incorrect—responses. Iterative questioning, verification, and the humility to double-check outputs underpin safe, effective use.
Those companies that treat training as a strategic, continuous function—not a one-off fix—will be best positioned. “Before you can lead in AI, you’ve got to understand it,” Blignaut emphasizes. “And that starts with asking the right questions—of your people, your data, and your systems.”
However, the path is not without challenges or risks:
Organizations willing to invest not only in current tools but also in continuous, strategically aligned education will position themselves not merely to survive, but to thrive in an AI-transformed economy. And, as Blignaut wisely concludes, “Before you can lead in AI, you’ve got to understand it—and that starts with asking the right questions.”
For enterprise IT leaders and HR strategists, that means one task is now more urgent than all others: to ensure AI readiness finally catches up to AI enthusiasm, before the gap becomes unbridgeable. Only then can the real promise—and power—of artificial intelligence in business be responsibly realized.
Source: SecurityBrief New Zealand Exclusive: Lumify warns AI readiness must catch up to enterprise adoption
Reality Check: AI’s Acceleration Outstrips Enterprise Understanding
In the corridors of enterprise IT and business strategy, this moment feels hauntingly familiar to cybersecurity’s boom years. Michael Blignaut, IT and process instructor at Lumify Work New Zealand (formerly Auldhouse, with DDLS in Australia), sounds the alarm: “Cybersecurity is our fastest growing area,” he states, noting an identical sense of urgency now gripping AI advancement. “Every single one of our partners—AWS, Microsoft, all of them—have got huge amounts of cybersecurity training.” That same energy is now being funneled into AI, with organizations scrambling to educate people even as they integrate AI tools into everyday operations.Lumify, Australasia’s largest corporate IT training provider, has nearly four decades of perspective on workplace upskilling in IT, project management, cybersecurity, and more recently, an expanding suite of AI-focused courses. It’s a vantage point that exposes a recurring challenge: the assumption that technological sophistication is synonymous with organizational readiness.
Driving Demand: AI Enters Mainstream Business Workflows
The explosion in AI adoption is tangible. Employees at all levels are experimenting daily with tools like Microsoft Copilot and ChatGPT, embedding them into email, productivity software, and business analytics. According to Blignaut, “Just using Copilot in emails, in Outlook and in Excel seems to get people very excited. It’s that basic end-user usage where there seems to be a lot of wow and excitement.”But behind the excitement lurk new risks. Many users either mistrust the tools—often due to “wrong answers”—or, conversely, swallow the output whole, risking overreliance. As Blignaut points out, “There’s also an overreliance: everything from ‘it can solve all our problems’ to ‘it’s not doing what I need.’” His comments echo findings from global research firms, such as Gartner and IDC, which have warned of gaps in AI literacy and the hazards of automation when humans disengage from critical review.
Governance and Privacy: The Unseen AI Adoption Challenge
The dark side of rapid mainstreaming, unsurprisingly, revolves around data privacy, governance, and responsible deployment. “AI governance is knowing what people are going to do with data...adopt AI and really use it to the potential benefit of the organisation,” Blignaut says. In regulated sectors or companies handling sensitive data—such as finance, healthcare, and government—the stakes could not be higher.This raises a crucial point: successful AI adoption is not merely about access to new tools, but about internal frameworks that anticipate misuse, bias, regulatory pitfalls, and workforce displacement. Lumify’s advice begins with assessment—utilizing AI readiness evaluations to determine where organizations really stand and what risks they must address before rollout.
For enterprise leaders, Blignaut urges, “It’s about thinking through your adoption strategies—and not being slow about putting in place really great implementation pathways.” This means clarifying who will use these tools, for what purposes, and under what safeguards.
Training for All: The Democratization of AI Skills
Unlike previous waves of enterprise tech, AI transformation is inherently democratizing: the upskilling mission extends to everyone, from executives shaping governance to frontline staff applying new tools. “I like having people in class with me,” Blignaut remarks, “but I think that’s where we’re going to settle: a bit of a mix.” The post-pandemic normalization of hybrid learning catalyzes this, with Lumify offering everything from one-day AI workshops to five-day deep dives, available in-person, online, or blended.This diversification is critical. While vendor certifications from giants like Microsoft or Amazon retain their value, organizations increasingly demand vendor-neutral, tool-agnostic programs. AI Certs, an internationally recognized certification body, has surged in prominence—offering credentials that outlast any single platform’s life cycle and adapt rapidly to change. Blignaut notes, “Keeping certifications current and standard is going to be a huge amount of work for them, but so far, so good.”
Prompting and Mindset: The Foundation of AI Proficiency
In the new AI workplace, one skill stands out as foundational: the ability to prompt effectively. Blignaut asserts, “To me, it’s always about the prompting. Being able to ask the right question, being able to really frame your prompt...across all platforms, being able to ask the right question or prompt—I think that’s where the challenge is going to be for everybody.”This notion is strongly supported by research. Misuse and misunderstanding of AI systems frequently trace back to poorly framed instructions or over-generalized queries. The emerging discipline of “prompt engineering” is now recognized as essential, with firms investing heavily in both technical and non-technical staff to learn this art.
Equally vital are critical thinking and iterative refinement. “AI does hallucinate,” Blignaut warns, echoing widespread reports of generative models providing plausible-sounding—but incorrect—responses. Iterative questioning, verification, and the humility to double-check outputs underpin safe, effective use.
Ethical and Job Market Impacts: Displacement With a Human Touch
Much of the debate around enterprise AI centers on job displacement versus job creation. Here, the Lumify perspective is optimistic, provided organizations adapt. AI “will be a net creator of jobs, but not without disruption,” Blignaut believes. Lumify’s training portfolio already addresses this, offering reskilling options for displaced workers, including non-technical tracks focused on digital literacy and adaptability—a move validated by World Economic Forum forecasts indicating millions of current jobs could be replaced by, but also reimagined with, AI in the coming decade.Those companies that treat training as a strategic, continuous function—not a one-off fix—will be best positioned. “Before you can lead in AI, you’ve got to understand it,” Blignaut emphasizes. “And that starts with asking the right questions—of your people, your data, and your systems.”
Critical Analysis: Lumify’s Approach and the Broader Landscape
The Lumify model triangulates three areas that, together, form the foundation for responsible and resilient AI adoption:1. Universal Upskilling
Rather than isolating AI literacy to a technical elite, Lumify’s programs reflect the reality that everyone has a stake, and potentially a touchpoint, in AI-driven change. Executives receive governance and ethics education, line-of-business managers hone prompt design, and technical staff extend their skills in deployment and integration. This breadth is a significant strength, addressing one of the most commonly cited failures of previous IT transformations: the exclusion of non-technical personnel.2. Assessment Before Adoption
The emphasis on readiness assessments mirrors best practices championed by the likes of Microsoft, NIST, and ISACA. By evaluating levels of AI maturity and risk before implementation, Lumify helps clients avoid costly missteps and identify where focused training is needed. This proactive approach distinguishes successful digital leaders from those playing perpetual catch-up.3. Vendor-Neutral Credentials
As the AI landscape fragments (with tools, frameworks, and best practices rapidly evolving), vendor-neutral certification becomes critical. These programs, including those by AI Certs, ensure that organizational investments in skills development remain relevant, and not tied to the fortunes of a single product. They offer resilience in the face of disruptive, unpredictable technological shifts.However, the path is not without challenges or risks:
- Skills Gap Lag: Despite best efforts, the rate at which the workforce can be upskilled may lag behind the pace of AI integration. Not every employee welcomes change, and the digital divide—in terms of confidence and baseline digital skills—remains real, especially outside metropolitan cities or in smaller organizations.
- Governance Complexity: As AI models grow more complex and training data more opaque, maintaining transparency, compliance, and explainability grows harder. Lumify’s focus on governance is well-placed, but regulatory frameworks themselves are still catching up, making it difficult for enterprises to feel their way forward with certainty.
- Overreliance and Trust: Increasing familiarity with AI tools brings new forms of risk—particularly a tendency to cede too much authority to automated outputs, or to believe AI carries inherent objectivity. The ongoing need for critical thinking, skepticism, and feedback loops cannot be overstated.
- Certification Fatigue: The proliferation of certifications—each promising to future-proof skills—risks confusing or overwhelming learners. Continuous revision of curricula and careful industry collaboration will be needed to ensure credentials remain valuable and not just another tick-box requirement.
Putting Readiness into Practice: Concrete Steps for Enterprises
For organizations determined to harness AI’s power without succumbing to its pitfalls, the Lumify case leads to clear, actionable recommendations:- Begin with Assessment: Use AI readiness tools (Lumify offers its own, and alternatives from vendors like Microsoft and Google have become widely available) to establish a baseline across departments.
- Strategize Adoption: Avoid the “one-size-fits-all” trap. Recognize that AI’s relevance, risks, and return on investment will differ for HR, finance, sales, and operations.
- Invest in Blended Learning: Combine short, practical workshops with deeper technical training, delivered flexibly (in-person, online, or hybrid) to maximize engagement and accommodate a range of learning preferences and schedules.
- Stay Technology-Agnostic: Supplement vendor-specific skills with tool-neutral certifications, ensuring agility as platforms and best practices change.
- Prioritize Prompting and Critical Thinking: Don’t treat “prompt engineering” as a technical afterthought. Make it a core competency, alongside courses on evidence evaluation, ethical reasoning, and iterative refinement.
- Build Reskilling Pathways: Proactively address job disruption by providing clear, accessible routes for employees to transition into adjacent or newly emerging roles—not just technical ones, but also in project management, communication, and digital fluency.
- Refresh Governance Regularly: As regulators update privacy and AI laws—OECD, EU AI Act, and local statutes—organizations must revisit policies regularly, ensuring that training and compliance efforts remain relevant.
The Road Ahead: Ensuring Lasting AI Leadership
The shift from AI as baffling buzzword to ubiquitous enabler is well underway. As enterprise adoption surges, the core insight from Lumify’s nearly 40 years in IT upskilling is unequivocal: technical readiness alone is not enough. True AI maturity demands that people—not just platforms—are empowered to ask good questions, manage new risks, and continuously adapt as tools and threats evolve.Organizations willing to invest not only in current tools but also in continuous, strategically aligned education will position themselves not merely to survive, but to thrive in an AI-transformed economy. And, as Blignaut wisely concludes, “Before you can lead in AI, you’ve got to understand it—and that starts with asking the right questions.”
For enterprise IT leaders and HR strategists, that means one task is now more urgent than all others: to ensure AI readiness finally catches up to AI enthusiasm, before the gap becomes unbridgeable. Only then can the real promise—and power—of artificial intelligence in business be responsibly realized.
Source: SecurityBrief New Zealand Exclusive: Lumify warns AI readiness must catch up to enterprise adoption
