The Tech Edge: Real Cost of Saying No to AI
I am a person who really cannot say no (absolutely not something I should be admitting in this very public blog!). You want to go abseiling? I’m there! Need someone to churn 40 liters or 10.5 gallons of cream into butter? I’m your girl! (I wish I could say this was not a true story, but it very much is). So I come to this blog with a sense of irony that I’m writing about organizations saying “no” to AI. But here’s the truth: We’re beyond that point where organizations can refuse or resist AI transformation. Businesses simply must adopt and adapt to the changing technological environment or risk being left behind.
During our recent Tech Edge episode, I had a conversation with AvePoint’s Chief Strategy and Marketing Officer, Mario Carvajal, about the real costs of AI resistance. And let me tell you, there is a lot that may hit close to home.
In our discussion, something became crystal clear: The cost of saying no to AI isn’t just about missing out on efficiency gains. It’s about watching your competitive edge slowly erode while maintaining expensive legacy systems that drain resources and limit agility. This is something organizations cannot sit back and watch happen.
The Amazon Effect: A Wake-Up Call
Remember when Amazon was “just” an online bookstore? Now, it’s the benchmark for personalized shopping experiences. Mario pointed out how traditional retail suffered by not keeping pace with AI-driven personalization. I’ll admit, I’m living proof of this impact. As an avid reader, I’ve switched to reading books electronically as my house simply cannot hold that many books! I’ve definitely fallen into (or perhaps willingly jumped into) the AI recommendation rabbit hole that comes every time I finish a book. The algorithm suggests new titles that are eerily perfect for my taste. “Add to cart, add to cart, add to cart” — I’m pretty sure I single-handedly keep book subscriptions afloat!
But here’s the thing: This isn’t just about my growing digital library. It’s about how AI has fundamentally transformed customer expectations across all industries. Whether you’re in retail, healthcare, or technology, the bar for personalized experiences keeps rising and I am here for it.
The Cost of Resistance: Risks and Missed Opportunities
Mario highlights several potential risks and costs associated with businesses deciding not to adopt AI:
- Competitive disadvantage. “Whoever leverages AI for efficiency, for data-driven decisions, making AI really at the center of their strategy, is going to win.” Mario emphasizes that companies not paying attention to AI risk being outpaced by their competitors.
- Missed revenue opportunities. He points out that AI can “truly unlock new revenue streams” for organizations, particularly by optimizing existing processes.
- Failure to enhance competitive position. AI offers opportunities for personalization and improvement in services and products. Mario stresses the importance of “personalization, improving the end-user experience, making sure that there are true outcomes of value.”
Think about healthcare providers who delayed integrating AI for diagnostics and personalized medicine. They’re not just missing out on technological advancement; they’re potentially facing higher operational costs and, more importantly, missing opportunities to improve patient care.
Breaking Down the Barriers
Through my conversations with other business leaders, I’ve identified four main roadblocks to AI adoption:
- Lack of knowledge in understanding AI technology and its benefits
- High initial investment in implementing and running AI solutions
- Disruption of existing processes leading to organizational change management challenges
- Data quality, privacy, and security concerns
When it comes to assessing whether the cost of implementing AI outweighs the potential benefits, Mario suggests a thorough cost-benefit analysis approach:
- Consider both direct and indirect benefits of AI.
- Evaluate short-term and long-term gains, including competitive positioning.
- Factor in the potential risks of not implementing AI, including security risks.
- Understand the quality of your data and how it impacts decision-making.
To overcome these barriers, it is important to educate organization about AI and its potential impacts, develop champions within the organization to facilitate change management, and proactively address data privacy and security concerns.
But here’s what fascinates me. In Australia, I’ve seen a positive shift in perspective. Organizations are moving from paralysis to pilots, from fear to focused experimentation. They’re starting to see AI not as a threat but as a tool for creating more time for what truly matters. I am sure this is also happening in other regions.
Key Takeaways for Businesses
What can you do, and where can you start? After deep discussions with Mario and other industry leaders, and based on my own experience in information management, here are my three key recommendations for organizations standing at the AI crossroads:
1. Start with Outcome-Focused Pilots
Instead of trying to boil the ocean, identify specific processes where AI can make an immediate impact. For example, if you’re in customer service, start with implementing AI-driven chatbots for common queries. Measure success through concrete metrics like response time improvement and customer satisfaction scores. This approach allows you to demonstrate value quickly while building organizational confidence in AI adoption. But don’t do anything until you have identified the outcome. Don’t implement for the sake of it, implement with value in mind.
2. Invest in Change Management, Not Just Technology
The success of AI implementation isn’t just about the technology — it’s about people. Create a network of AI champions across different departments who can educate and inspire their colleagues. Develop a clear communication strategy that emphasizes how AI will enhance (not replace) human capabilities. Set up regular training sessions and feedback loops to address concerns and share success stories. This human-centric approach helps overcome the “disruption fear” that Mario identified as a major barrier. Giving people the opportunity to share their own knowledge and learn from others has a significant impact on success outcomes.
3. Build a Data-First Foundation
Before diving into advanced AI applications, ensure your organization has a solid data infrastructure. This means conducting a thorough audit of your data quality, implementing robust data governance policies, and establishing clear protocols for data privacy and security. As Mario emphasized, the quality of your data directly impacts the effectiveness of your AI initiatives. Consider starting with a data cleanup project and implementing automated data quality monitoring tools. This foundation will not only support your AI initiative but also help address security concerns that often hold organizations back. You will not have a successful AI implementation without good quality, secured data. There is no way around this.
The Way Forward: Embracing AI
The conversation about AI adoption isn’t really about whether to adopt anymore — that ship has sailed. It’s about how to adopt intelligently and responsibly. As someone who’s witnessed both the hesitation and the transformation firsthand, I can tell you that the cost of saying no to AI far outweighs the challenges of implementation.
Those who embrace this technology strategically and responsibly will be best positioned for innovation capacity and future growth opportunities. As we move forward, the ability to effectively integrate AI into business strategies will undoubtedly become a key differentiator in the market. Just like I couldn’t say no to that impromptu abseiling adventure, organizations can no longer afford to say no to AI.
The difference is, with AI, we’re not just seeking thrills — we’re securing our future in an increasingly competitive landscape.
Check out this episode and more here: The Tech Edge — Ticker
Alyssa Blackburn is the Director of Records & Information Strategy at AvePoint, where she helps organisations achieve business value from their information. In her role, Alyssa provides records and information consulting services as well as system implementations, allowing customers to optimise the structure of their information to maximize business benefits while meeting data governance and compliance objectives. With 20 years of experience in the information management industry, Alyssa has worked with both public and private sector organisations to deliver guidance for information management success in the digital age. She is responsible for the development of AvePoint’s information management solution, and has been involved with implementing our records management solution with government agencies and commercial clients. Alyssa is actively involved in the information management industry and has spoken at a number of events including at Inforum 2016 in Perth. She has been published in the RIMPA IQ magazine and recently won the 2016 award article of the year for the RIMPA IQ magazine for her article titled, "Why you need to think differently about information management."
