Why Most AI Projects Never Make It to Production (And a Simple Framework to Fix That)

Tooba Jalalidil, AI Architect Manager at Accenture and Co-Founder of Seekario.ai, joined the Women in Digital community to share a practical, no-jargon approach to building AI business cases that actually get off the ground.

We’ve all seen it happen. A team gets excited about AI, runs a flashy proof of concept, presents a compelling demo, and then… nothing. The project quietly dies somewhere between “that looked amazing” and “so, who’s going to build this for real?”

It turns out, this isn’t a rare experience. Across the industry, industry estimates suggest most AI projects never make it to production. And the problem isn’t usually the technology. It’s the business case.

That’s exactly what Tooba Jalalidil unpacked in her Women in Digital masterclass, From Idea to Execution: How to Build and Lead AI Business Cases. Drawing on more than a decade of experience in AI, ML, and data strategy, plus her dual perspective as both an enterprise leader at Accenture and the co-founder of AI startup Seekario.ai, Tooba shared a rigorous, human-centred framework for evaluating which AI ideas are worth pursuing, and which ones deserve a hard pass.

Stop solving for “AI wishes.” Start solving for real pain.

Before you write a single user story or spin up a proof of concept, Tooba says there’s one critical step most teams skip: talking to the people who will actually use the tool.

Too often, AI projects start with an executive’s enthusiasm (“we need to do something with AI”) rather than a frontline team’s genuine frustration. The result? Solutions that look impressive on a slide deck but add work, instead of removing it.

Tooba’s advice is refreshingly practical. Shadow real users. Sit with them while they do their jobs. Ask one simple question: “If you had an AI teammate for six months, what would you ask it to take off your plate first?”

If you can’t write a one-sentence problem statement from the user’s perspective, tied to a specific role and a measurable pain point, you’re not ready to design a POC.

The DVFF framework: a pre-flight checklist for AI

The centrepiece of Tooba’s masterclass was the DVFF framework, a structured way to pressure-test any AI initiative before committing time, budget, and team energy. It stands for Desirability, Viability, Feasibility, and Finance, and it works like a pre-flight checklist.

Desirability: Does anyone actually want this?

This isn’t about whether 100 people could use it. It’s about how much time or pain it genuinely removes. An AI tool that saves 100 analysts 30 minutes a day is a very different proposition from one that saves 100 people 60 seconds a month. If the audience is small and the impact is marginal, the desirability score should be low, no matter how clever the technology is.

Viability: What happens if we don’t build it?

If the honest answer is “nothing material breaks,” you’re probably looking at a nice-to-have, not a strategic priority. Strong viability statements connect directly to revenue, risk, or customer outcomes. Think: “Without this, our new sales reps take nine months to ramp up, costing an estimated $1.2M in lost bookings annually.”

Feasibility: Do we actually have what we need?

This means getting honest about data quality, infrastructure, and team skills. A POC built on historical call transcripts will fall apart if half the real-world calls happen on mobile phones that aren’t recorded. And if your platform only supports nightly batch loads but the use case needs near real-time data, the cost and complexity may outweigh the value.

Team capability is often the hidden constraint. Tooba flagged a common pattern: capable engineers without deep data science or AI engineering experience push raw data into large language models, then compensate for noisy outputs by chaining more agents and prompts, driving up costs without achieving reliable results.

Finance: Can you explain this in dollars?

If you can’t translate the value into a language your finance team understands, your project is vulnerable. Vague promises of “productivity” invite hard questions about why existing tools (like Microsoft Copilot or standard automation) can’t do the same thing. Be specific: hours saved per role per month, reduced churn, higher conversion rates, and avoided infrastructure spend.

Turning scores into decisions

One of the most useful parts of Tooba’s session was her guidance on how to actually use the framework in practice. She recommends running a short scoring workshop where stakeholders independently rate each dimension before comparing results.

Define three to five questions under each DVFF pillar and score them from zero to two. Then look at the total, but also pay attention to weak spots. A project with strong desirability and feasibility, but a finance score near zero, is likely to be killed at funding review, no matter how exciting the demo looked.

Set clear thresholds in advance. For example, on a scale of zero to 24: a score below 13 means park it or re-scope; 13 to 18 means investigate further; 19 and above means you have a genuine candidate for a proof of concept.

The people piece matters most

Tooba closed with something that resonated deeply with our community: even the strongest DVFF score won’t save an AI initiative if you underinvest in adoption. Budget for training, documentation, internal champions, and support. In a world where most people now have experience with consumer-grade AI tools like ChatGPT and Claude, anything less intuitive will struggle to gain traction.

The real takeaway? Stop chasing shiny AI concepts. Back a smaller number of initiatives that are deeply tied to real problems, technically grounded, and financially defensible. That’s how you move from impressive demos to sustainable, live systems.

About Tooba Jalalidil

Tooba Jalalidil is a Manager at Accenture, where she leads the design and delivery of Generative AI solutions, and the Co-Founder of Seekario.ai, where she is democratising AI for job seekers. She combines enterprise rigour with startup agility, bringing over a decade of experience in AI, ML, and data strategy to drive responsible innovation. Tooba is also a passionate advocate for diversity in STEM and an active mentor, dedicated to empowering the next generation of leaders across the technology community.

This masterclass was hosted as part of the Women in Digital members’ webinar series. Want access to sessions like this? Learn more about WID membership.

Team Next Gen, the robots are coming — and impatience won’t save you

Holly Hunt, Founder & CEO of Women in Digital, shares her reflections from the Great Generational Debate.

At Women in Digital’s Great Generational Debate, we brought together Team Legacy (Gen X and Boomers) and Team Next Gen (Gen Z and Alpha) to do something the workplace rarely makes space for — genuinely listen to each other. There were no winners. That was never the point. But walking away, I couldn’t shake a sense of unease.

As a Millennial, I found myself caught in the middle — nodding along to both sides. I related to Team Legacy’s belief in rolling up your sleeves and earning your seat at the table. I also respected Team Next Gen’s clarity about their own worth, their appetite for purpose, and their willingness to challenge systems that frankly do need challenging. But there is a tension that the debate surfaced that I don’t think we can afford to gloss over.

The uncomfortable truth about timing

Team Next Gen enters the workforce with higher expectations than any generation before them — and in many ways, rightly so. They want to understand the why behind commercial decisions. They want to be part of strategy conversations early. They will move roles if growth stalls. They have clearly defined boundaries and they are not afraid to use them.

These are not inherently bad qualities. In fact, several are admirable.

The problem is the timing.

AI is not a future threat — it is a present one. The entry-level roles that have traditionally been the training ground for careers in technology are already being replaced. The graduate pathway that Team Legacy walked, and that Millennials like me benefited from, looks fundamentally different today. In that environment, the expectations Team Next Gen are bringing to the table carry real
risk. When a junior employee signals early that they will leave if they aren’t in strategy conversations, or if the why isn’t clearly communicated — the cold, commercial reality is that it diminishes a leader’s incentive to invest in them. Mentorship, sponsorship, and genuine career development require time. And time-poor leaders will direct that investment where they see loyalty and commitment in return. Team Next Gen may be inadvertently doing themselves out of the very careers they want.

What this generation gets right

This is not a dismissal of Team Next Gen — far from it. One of the most memorable moments of the debate was a Next Gen panellist describing life as a game of chess: a game of strategy where you can never focus on just one piece. It was sharp, considered, and insightful.

Team Legacy openly admired their self-awareness and their refusal to derive all sense of worth from a job title. That evolution matters.

And they are right that the systems that got us here are not necessarily the systems that will take us forward.

The bridge worth building

The generational divide in the workplace is not a problem to be solved by one side conceding to the other. But it does require honesty.

For Team Next Gen: there is real value in seasons of intensity — in getting on with the job before you fully understand the strategy behind it, in demonstrating commitment before demanding flexibility. Adapting to the commercial realities of work, particularly in a rapidly shifting labour market, is not selling out. It is survival — and ultimately, it is how you build the influence to change the things that need changing.

For Team Legacy: the low seasons matter too. Supporting interests outside of work, investing in the development of junior talent even when the return is uncertain, and genuinely learning from a generation that has grown up with the world at their fingertips — literally — is not weakness. It is leadership.

As for me — I make no apologies for loving my work. For finding purpose in it. For believing that a career built with commitment and pride is something worth having. And I don’t think
Team Next Gen should apologise for wanting more from life than work alone. But in a world where machines are quietly taking the entry points, this generation cannot afford to let impatience cost them the career they are capable of building.

The robots are not waiting. Neither should they.

Leadership in the Age of AI: Why the Human Equation Has Never Mattered More

Artificial intelligence is rewriting the rules of almost every industry in this country. From the mining giants of Western Australia to the fintech start-ups crowding Sydney’s CBD, no sector is untouched. 

Yet for all the breathless commentary about automation, machine learning and the imminent obsolescence of white-collar work, Australia’s most thoughtful business leaders are arriving at a counterintuitive conclusion: the AI era will be won or lost on fundamentally human terms.

That was the unmistakable message to emerge from this year’s Women in Digital International Women’s Day gatherings in Brisbane, Sydney and Melbourne, three events that brought together leaders across multiple generations to confront one of the defining questions of our working lives. 

Not “what will AI do to our jobs?” but rather, “what kind of leaders do we need to navigate what comes next?”

The answers were more nuanced, and more hopeful, than the AI doomsayers might expect.

The Weight of Earned Wisdom

To understand where we are headed, it helps to understand where we have been. Generation X, who entered the workforce in the analogue era, built their careers through the digital revolution.  They did not merely adapt to change.  Gen X were key drivers of that change.

In industries like technology, where women were routinely underestimated, advancement demanded more than competence. It required the kind of persistent, credibility-building effort that reshapes institutions from the inside.  

The parental leave entitlements that younger Australians can take for granted now, the flexibility policies that have become standard in competitive workplaces, the growing acknowledgement of mental health as a legitimate workplace concern with none of this happening spontaneously. It was hard-won, over decades by professionals who were willing to challenge a status quo that was not built with them in mind.

Hence, that legacy is relevant directly to the AI transformation.  Navigating disruption with genuine, structural, unsettling disruption, requires exactly the qualities and characterisitics working generations of the seventies, eighties, nineties and early 2000s forged.  The qualities of resilience, institutional knowledge and informed judgement that only comes from having weathered profound setbacks and changes before.

The Brilliance of Questioning Everything

And yet, experience alone will not be enough. The younger professionals now entering Australia’s workforce bring something equally essential to the table, which is routinely misread by the leaders who need it most.

When a millennial or Gen Z employee asks why a decision was made, or pushes back on a process that has always been done a certain way, that is not insubordination. It is precisely the disposition that thriving in an AI-powered economy demands. These are professionals who will not accept inherited assumptions, who want and expect transparency from leadership and who want to understand the purpose behind their work, not simply to execute tasks without context. And that’s tough for managers and leaders.

In an era where AI can handle an ever-expanding range of routine cognitive work, the humans who will add the most value are those who question, synthesise and reimagine. 

Leaders who channel that energy effectively will build genuinely adaptive people who will grow organisations and beyond. Those who dismiss it as entitlement will find themselves leading teams that are neither innovative nor engaged.  In technology, retention and growth of our workforce are instrumental to organisational success.  Having the right people, in the right jobs at the right time, enables greater productivity which in turn drives performance and profitability. 

What Leadership Actually Requires Now

The best leaders of this era will be those who create environments where ideas are not gatekept by seniority, where psychological safety is genuine, curiosity is rewarded and the reasoning behind strategic decisions is shared openly.  That is challenging for some managers and leaders who have in previous times worked where organisational strategies and plans are kept behind closed doors.  Complicating this further, governance structures, shareholder policies and competitive advantage.

So perhaps, it comes back to a return to first principles. Workflows transform. But ownership of outcomes, continuous learning, engagement and a willingness to do the hard work, with these remain universal and non-negotiable. No algorithm substitutes for commitment and persistence.

Australia’s workplaces are at their most powerful and most productive when experience and fresh thinking operate together, not in opposition. The organisations that grasp this will be the ones who build cultures of genuine intergenerational collaboration and will be best placed to lead in the decade ahead.

The age of AI is here. The leaders who will define this generational change will be human-centric, human-positive and human-motivated.

Artificial Intelligence – Opportunity Brings Immense Responsibility

There is no doubt we are working and living in a time of exponential change, where technological advancements are moving faster than ever before.

Whilst the crossroad of technology, leadership and generational forces is reshaping the modern workplace, AI is rapidly transforming how organisations operate with equity, representation, participation, belonging, and leadership evolving just as quickly.  To add, at Women in Digital’s International Women’s Day events held in Brisbane, Sydney and Melbourne, it is evident these subjects are only gaining momentum.

Panel discussions featuring senior leaders across science, data, technology, cybersecurity and global industry reinforcing the future of work will be shaped as much by human connection and culture as by technological innovations and advancements.

The evidence overwhelmingly supporting current challenges and opportunities are not simply about adaptation, but navigating profound shifts in how people work, how career paths evolve and how opportunities are created and shared.

At Women in Digital, we strive to ensure that the conversations inspired by this year’s IWD events are not tokenistic and that accountable actions are implemented in organisations across Australia. Women in Digital has prepared articles summarising the key takeaways and trends important to women, our male allies and business leaders across the digital and tech sectors.

Artificial Intelligence Opportunity

It is widely believed that Artificial Intelligence (AI) is the defining shift of the next decade.  AI represents a structural shift in how work is performed, how decisions are made and how value is created.  AI will impact the size of workforces and their capability. Roles that centre on repetitive processes are more vulnerable and open to immense change.  Some may evolve, many will disappear.

A key theme of our speakers this year highlighted that AI will only elevate the importance of human connection and capabilities and nothing will ever replace the enduring value of hard work, persistence and continuous learning.

The most effective strategy for navigating AI disruption is engaging and learning. Professionals who take the time to understand AI tools, experiment with them, and integrate them into their work will be better positioned than those who resist change. Many organisations are already investing heavily in workforce education – providing employees with access to AI tools and training programs that build familiarity and confidence.

These efforts serve a critical purpose: helping employees see AI not as a threat but as a tool for augmentation and productivity. In many cases, AI can eliminate repetitive tasks and allow professionals to focus on more creative, strategic, and human-centered work. In this new environment, the most valuable professionals will be those who combine technological literacy with human judgment with human connectivity.

As AI adoption accelerates, another issue becomes increasingly important: governance. AI systems can amplify existing biases if they are developed without diverse perspectives and ethical oversight.  This makes representation within AI development teams especially important.If the individuals designing AI systems do not reflect the diversity of the societies they serve, those systems may inadvertently reproduce existing inequalities.

Strong governance frameworks, ethical oversight, and inclusive development practices are therefore essential. Organisations must treat AI not simply as a technology initiative but as a responsibility that requires careful stewardship. 

Professionals who will thrive in an AI-driven world need to focus on developing the following skills:

Curiosity.
Individuals must take responsibility for understanding how AI tools work and how they can be applied. Continuous learning will become a professional necessity.

Critical Thinking.
AI systems generate outputs, but humans must assess their accuracy, relevance, and implications.

Creativity.
Original thinking, imagination, and the ability to see new possibilities remain uniquely human strengths.

Entrepreneurial Mindset.
Understanding how technology can solve real-world problems will create new opportunities for innovation and value creation.

Ethical Awareness.
As AI becomes embedded in decision-making systems, governance, transparency, and societal impact will become central leadership responsibilities.

Human Connectedness.
An AI-driven world will not be defined by the technology that surrounds us, but by our ability to use it to deepen empathy, strengthen relationships and preserve the human experience at the core of leadership and innovation within our professional and personal lives.

What Next?

The transition to an AI-driven future is not a passive event; it demands active participation and conscious leadership. The responsibility to harness AI as a force for good with one that promotes augmentation, productivity, and, crucially, equitable outcome, will rest with every individual and every organisation.

At Women in Digital, we hope that you allow the energy and insights from this International Women’s Day, serve you as a catalyst for action.

For business leaders, this means actively investing in governance frameworks, inclusive development teams, and comprehensive workforce education. For professionals, it means cultivating the essential human skills of curiosity, critical thinking, creativity and ethical awareness, the human traits that AI can never replace.