Are you a C-suite exec still grappling with the basics of AI? Are you aware that some companies are so far ahead they’re daring to say, “Google, move over”?
As AI adoption becomes imperative, standing on the sideline is no longer a neutral act—it’s a step backward.
It’s pretty safe to say that this high-stakes environment isn’t for spectators.
Based on a survey of nearly 100 C-suite professionals, conducted by our very own Brett St Clair, we’re taking a look at the current state of Generative AI (Gen AI) in the corporate world and offering actionable insights.
The Current Perception of Gen AI in the Business World
When it comes to Generative AI, the spectrum of readiness and perception among companies is broad:
- What’s AI?: A surprising 24% of C-suite execs are still questioning the basics. If you’re among them, it’s high time for a deep dive.
- Experimenting with Models: A significant 41% are in the sandbox stage, playing around with models using a handful of data scientists. They’re getting their feet wet, but have a long journey ahead.
- Diving into MLOps: About 14% are somewhat advanced, building an MLOps and Data Environment. They’re the ones breaking ground.
- Plan Without Execution: 8% have well-articulated plans but are stuck at the execution stage due to a lack of skills or tools.
- We’ve Nailed It: An ambitious 14% believe they’re ready to surpass industry giants like Google in AI capabilities.
The majority are in the testing phase. So the race has begun – but it’s far from over.
The Data Preparedness Conundrum
Data is the fuel for AI, and without a stable supply, you’re going nowhere:
- Fragmented Data: For 43%, the data is so disorganised that even basic insights are challenging to glean, let alone fine-tuning AI models.
- Data-Ready, What Next?: About 45% have their data ducks in a row but need to advance their ability to deploy models via MLOps.
- Budget and Time Constraints: For 13% of respondents, organisational red tape is the obstacle, making projects longer to initiate and complete.
The findings reveal that unless there’s some form of data readiness, any advancement in AI remains a pipe dream.
The focus should be on removing bottlenecks.
The Intellectual Property Dilemma
Concerns over intellectual property are running high:
- Cost Over IP: For 10%, especially startups, costs are a bigger concern than IP.
- Public Models and IP: Around 7% discover they might be inadvertently training public models with their business IP.
- Governance First: A massive 76% emphasise that governance and security concerns must be addressed before diving into AI.
Governance isn’t a buzzword; it’s a prerequisite for the vast majority of C-suite leaders.
The Speed of Adoption and Ethical Considerations
The path to AI adoption isn’t straightforward:
- Exploration Without Direction: 50% of the respondents are at an investigational stage but lack a clear path forward.
- Under-the-Table AI Use: For 8%, governance is an afterthought; they’ve been using AI tools without official sanction.
- Ethics and Governance Centric: A solid 39% are making a concerted effort to align AI with ethical guidelines and governance.
Speed of adoption is tightly woven with ethics and governance, making them non-negotiable aspects.
Quick Wins and Low-Hanging Fruits
- AI-Generated Assets: 16% see immediate gains here.
- Fine-Tuning Language Models: For 53%, this is the starting point for their Gen AI journey.
- Intelligent Decision-making: About 32% are looking at sophisticated AI tools for business decisions.
Most C-suite execs see fine-tuning their existing language models as the quickest path to realising Gen AI’s benefits.
How To Move Forward
The landscape of Generative AI is a terrain brimming with opportunities – and pitfalls.
The key points, as seen from the C-suite vantage, are data readiness and governance. Whether you’re a novice or a pioneer in AI adoption, the time to accelerate your journey is now.