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Real value of artificial intelligence lies in turning data into insights

The real value of artificial intelligence lies in transforming vast volumes of data into meaningful insights that drive faster, smarter decision-making. Moving beyond basic automation, organisations can harness AI-powered analytics and real-time data processing to shift from retrospective reporting to predictive, insight-led strategies. By unlocking actionable intelligence from complex datasets, businesses gain the agility and clarity needed to respond to changing markets and deliver measurable impact.

Artificial intelligence (AI) may dominate business conversations, but many organisations are still struggling to move beyond experimentation and pilot projects. According to Mike Moloney, pre-sales engineer at Conscia Ireland, businesses need to look beyond AI-powered assistants and focus instead on how AI can transform the way they use and understand their data.

Conscia Ireland brings together the expertise of established technology businesses including PlanNet 21, Agile Networks and eCom Solutions, now unified under Conscia, which has a strong presence across Europe. The company works with organisations across sectors including healthcare, government, financial services and enterprise, helping them modernise their infrastructure, networking and security capabilities.

Dominant

“Every executive agenda globally is dominated by AI at the moment,” said Moloney. “There’s a gap that’s emerged between the hype surrounding AI and AI’s actual operational utility. True enterprise transformation is not happening in AI apps that handle basic automated tasks like email responses and things like that.

“We need to turn the focus to where the real business impact is, and that’s using AI-native infrastructure, turning raw data into actual business velocity through the use of telemetry, and discovering actual insights from that.”

For many organisations, that means rethinking their relationship with data.

“Historically, enterprises would have been very data rich but insight poor,” he said. “They would have been relying heavily on static, retrospective reporting. That’s shifted now with AI. Today’s moving markets have created a shift toward real-time predictive analytics, and that allows leadership teams to make better-informed decisions and execute rapid responses in changing markets.”

Unprecedented

The need for those capabilities is becoming increasingly apparent across industries. Whether in healthcare, manufacturing or financial services, organisations are generating unprecedented volumes of information that must be analysed in real time.

“We see this now in healthcare and the public sector, where we need to guarantee predictable, mission-critical application performance. Clinicians, for example, can’t lose access to electronic health records. We see it in life sciences and manufacturing, managing automated onboarding and ingesting real-time telemetry from thousands of sensors to keep production lines going and optimise supply chains. In finance, we’re looking at highly volatile markets where assets and communications are all occurring within milliseconds. All of this has to be ingested and correlated in real time, and people working in that space can’t keep up with that.”

According to Moloney, unlocking the value of that information requires modern infrastructure rather than simply layering AI tools on top of existing systems.

“The modern AI strategy can’t sit on legacy architecture,” he said. “To extract this value from data while still maintaining compliance and security, the modern enterprise needs an integrated stack. Data, cloud, cybersecurity and networking all need to be pulled together. With AI as part of the infrastructure, it can ingest this, correlate it and comprehend it in real time. We’re faster to resolution and faster to decision-making that way.”

Security is another area where AI is having a growing impact.

Rather than waiting for problems to emerge, organisations are increasingly using AI to detect issues before they affect users or operations.

“Instead of waiting for the need for human intervention, AI network architecture utilises machine learning and allows you to baseline what’s normal and what good looks like,” said Moloney. “We can transform the network from a passive pipe into a proactive sensor.

It correlates all of this data, isolates anomalies, initiates closed-loop automation and resolves issues in real time while still maintaining guardrails.”

Upskilling

Despite concerns that AI could replace workers, Moloney believes the technology will instead change the way people work and create opportunities for upskilling.

“Intent and accountability are a big thing here,” he said. “While AI can pick up the workload, ultimately someone still needs to ask it to do the task and needs to be accountable for the outcome. There’s a little bit of fear around it that it’s going to displace a lot of people. But as people become more informed around new technologies, you lean into it and it opens up other opportunities.”

For Conscia Ireland, the future of AI lies not in isolated applications but in building intelligent, integrated infrastructure that allows organisations to make faster, smarter decisions.

“AI is not a tech industry luxury anymore,” said Moloney. “We’re seeing operational transformation happening across wider economies. By integrating all of this into a unified strategy, enterprises can transition from manual, reactive firefighting and move towards a more AI-driven future.”

Juniper Mist (now part of Hewlett Packard Enterprise) is an AI-native cloud networking platform designed to simplify IT operations and optimize end-user experiences. It leverages AI and machine learning to automate Wi-Fi, wired, and SD-WAN networks while providing deep, telemetry-driven insights.