- 95% of developers say AI should explain its reasoning so it can validate answers
- They fear that manually explaining context will waste time
- AI could unlock observability data, but first we need to tackle silos
A new study from Grafana Labs suggests that developers are very eager to adopt artificial intelligence, with 92% seeing its value in detecting problems before downtime and 91% valuing it for prediction and root cause analysis.
While the benefits are clear, developers still lack confidence when it comes to using AI: 15% don’t trust autonomous actions, and an overwhelming majority (95%) prefer AI to explain its reasoning in order to understand how it achieved its outcome.
And while businesses grapple with security, compliance, and inadequate infrastructure, developers themselves are most concerned about having to manually provide context, undermining AI’s promise of effectiveness.
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Developers are ready for the moment when AI can actually increase productivity
“Practitioners want reliable AI that reduces work and helps them move forward faster,” wrote Marc Chipouras, vice president of emerging products.
Outlining the roadmap ahead, Grafana Labs explains that developers want AI assistance and transparency to mature before autonomy becomes the default.
Elsewhere, the report also highlights that companies struggle with observability. Three-quarters (77%) of those with centralized observability say they have saved time or money, but many still struggle with complex, siled setups.
It is this observability that is expected to see increased spending over the next year as executives expect more efficient operations.
The report also outlines how AI could help in this area, with a third (30%) of workers citing alert fatigue as the biggest barrier to faster incident response.
Looking ahead, it is clear that these two business priorities are closely linked. With effective observability generating huge volumes of data, an AI layer on top can make it easier for workers to identify patterns and reduce downtime.
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