Gartner Technology Adoption 2024
An Opinion
In this week’s blog post, we explore Gartner’s 2024 Technology Adoption Roadmap for Data and Analytics. The schematic linked here (Technology Adoption Roadmap for Data and Analytics Functions for 2024 – Gartner) outlines the three core pillars of AI readiness:
- AI-ready data
- Analytics and AI
- AI-ready governance
Join us as we unpack Gartner’s key takeaways, and share our insights as an independent technology boutique.
Pilot and Prove Approach to AI-Readiness
Gartner highlights a major trend: organisations are increasingly adopting a “pilot and prove” strategy for AI readiness. This is logical, as AI has reached the “peak of inflated expectations” (per Gartner’s Hype Cycle for Emerging Technologies). AI’s transformative impact touches every facet of business – from data processing to architecture – so it is essential for businesses to test and prioritise the key components that work best for them. According to Gartner, 75% of surveyed technologies are in pilot stages, 22% are in deployment, and 3% are planned.
In our own work with clients in transportation and advertising, we’ve observed similar trends, with even higher pilot activity: 85% in pilot, 13% deployed, and 2% planned.
Proof-of-concept (PoC) projects are invaluable for companies looking to experiment with AI and uncover new opportunities. We strongly recommend partnering with leading technology firms and participating in industry events to exchange ideas and gain fresh insights. In fact, one of our team members recently attended the Data and AI Summit in San Francisco, connecting with professionals across sectors like semiconductors and manufacturing. The value that industry-diverse teams had obtained underscored the profound impact that experimentation and PoCs can have, confirming our perspective on the value of looking forward. Staying engaged with the community isn’t just beneficial – it’s essential.
Talent Shortage
A pressing issue highlighted by Gartner is that 44% of technologies are stalled due to talent shortages. We see this challenge resonating across industries, but there are strategic ways to overcome it:
Hire for potential: Instead of searching endlessly for the “perfect” candidate, seek out motivated individuals with a hunger to learn. A passionate, fast learner can bridge even multi-year gaps in experience remarkably quickly.
Upskill your current team: Investing in training for your existing employees can be faster and more cost-effective than bringing in fresh external hires – and it significantly boosts team loyalty. When you invest in your people, everyone wins.
Leverage talent from adjacent fields: Professionals from related fields may be eager to pivot into AI, providing a faster route to onboard experienced talent.
Speed and Agility
According to Gartner, 83% of AI-ready technologies enhance organisational agility – we agree that this flexibility is a critical edge in today’s fast-paced market. We’ve witnessed firsthand how strategic and targeted tech stack upgrades can yield substantial ROI. One of our clients in the advertising sector enhanced their reporting and dashboard efficiencies by 3x in just a few months through targeted tech enhancements. Quick wins in such crucial areas can lead to outsized impacts. Enhancing speed and agility helps an organisation level up from just staying competitive, to setting the pace in the market.
AI-Ready Data
Leveraging the full potential of AI starts with readying your data. AI models, data engines, and large language models (LLMs) are only as powerful as the data that fuels them. While many organisations treat data readiness as a challenge, we believe it is really an opportunity. Much like the Big Data revolution of 2013, the smartest organisations will seize this moment to cleanse and harmonise their data ecosystem. By streamlining your data for the AI era, you will be able to move faster than the competition and extract the benefits of new systems as they emerge.
We’re already seeing this play out with transport industry clients. Previous investment by one of our partners in a state-of-the-art data powerhouse to unify complex datasets in real-time has allowed rapid development and adoption of an AI-powered rail simulation tool projected to save 5K working hours in the first year alone. In short, train operators that were prepared are reaping substantial benefits right now. Whilst other providers can eventually catch up in terms of technology, by then the impact of the competitive gap will already be acutely felt.
Parting Thoughts
While there are more valuable insights in the full report, we encourage you to explore it further. The key takeaway is that companies are actively experimenting with AI technologies and evaluating their business impact. The potential benefits—revenue growth, efficiency improvements, and tech stack modernization—are immense. While the full report is brimming with invaluable insights—and we highly recommend delving into it—the key takeaway is clear: Companies are actively experimenting with AI technologies and assessing their business impact. The potential benefits are enormous:
- Revenue growth
- Enhanced Efficiency
- Modernised Tech Stacks
We urge you to dive in headfirst. Engage with your teams and partners, attend industry events, and seek guidance from technology leaders. At DAS, we’re passionate about innovation and growth, and we’re here to support you. Feel free to reach out to us for a conversation about your AI journey and future aspirations, let’s shape the future together.
Don’t sit back and watch the AI revolution unfold – be a part of it!
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