Enterprises will need to nail and scale complex data management

Zuzanna Stamirowska, CEO and co-founder, Pathway

“2025 will see enterprise AI transition from proof of concept to production, with a sharper focus on ROI. However, challenges like data management, privacy, and updates will intensify. To succeed, organisations must feed enterprise data into LLMs, ensuring models can contextualise and retrieve complex data at speed. Live AI will gain prominence, enabling smarter handling of fresh structured and unstructured data for operational success.”

Ellison Anne Williams, founder and CEO, Enveil  

“While the promise of AI remains substantial, its value is rooted in an organisation’s ability to access and use rich, relevant data for evaluation and training. This core need will be abundantly clear as AI tools move from sandboxes to operational environments where the stakes are much higher.

“For cyber leaders, this will also amplify the need to ensure that data sources can be used in a manner that prioritises both security and privacy. If not, the value business and mission value delivered by AI will be unable to overcome the impact of risks it introduced.”

Andrew Beal, chief architect, Markerstudy

“AI’s explosive growth has elevated data’s importance, but most organisations’ data platforms were built for MI and reporting, not AI. While AI requires raw, unstructured data, traditional platforms aggregate and structure data, losing its unique value.

“GenAI will unlock unstructured data’s potential, turning documents, images, and videos into valuable resources and driving a need for robust data ecosystems.

“In 2025, security, governance, and ethical practices will become critical. Tools like data catalogues and tagging will ensure data is well-managed, while organisations will need frameworks to address privacy, bias, and ethical AI applications.”

The democratisation of data access continues…

Martin Brunthaler, chief technology officer and co-founder, Adverity 

“Data democratisation will reach new heights, fundamentally reshaping how businesses operate. We can expect to see more brands and agencies taking steps to ensure data is easily and quickly available: empowering their teams to take full control of insights without heavily relying on IT or data engineers, so IT can establish secure, scalable systems to maintain organisational standards and focus on other strategic, more valuable initiatives.

“Features like conversational data interfaces, smart recommendations, and customisable micro-apps will become standard, making accessing and acting on data simpler and faster.

“Data democratisation will play a pivotal role in enabling business transformation at scale, helping companies to stay competitive in a rapidly changing world.”

Analytics: Dashboards are dead

Derek Slager, CTO and co-founder, Amperity 

“Dashboards are dead – Generative AI-powered tools offering the ability to answer the questions that matter on-the-fly will be the new surface for analytics and decision making.”

Hybrid models will power Big Data

Enrico Signoretti, VP of product and partnerships, Cubbit

“Unstructured data will grow steadily in 2025, making data management essential for storage and value extraction. Organisations will tackle data growth with CapEx, OpEx, and optimisation, favouring hybrid cloud and STaaS models. Advances in visibility will address challenges like data silos from hybrid and multi-cloud usage, with S3 data lakes emerging as a key solution for improved accessibility and security management.”

Chris Hall, CPO, Precisely

“Disruptive technologies like AI and cloud adoption are driving demand for simplified, trusted data access. To meet this, organisations will converge fragmented data ecosystems and adopt unified data integrity strategies across hybrid environments. Integrated data management reduces costs, ensures governance, and enables data teams with self-service access to power analytics and AI initiatives.”

The post 2025 Informed: Big Data predictions for the year ahead appeared first on TechInformed.

The role of GenAI in reshaping how we interpret and leverage information cannot be overstated, and it is truly proving to be a differentiator, further separating early adopters and laggards. Traditionally, data has been siloed within specialist teams—scientists, engineers, and analysts—leading to bottlenecks that stifle agility and slow decision-making. By implementing GenAI products, businesses can break down these silos by enabling users at all levels to engage directly with data, putting data insights in the hands of every business user, engineer and application builder. When leveraging GenAI for data analytics, businesses are able to guide and automate certain tasks, cutting down the time this would normally take between different data teams, which in turn empowers users to be more productive and help employees serve themselves more efficiently.

Early adopters of GenAI for data analytics, like EcoLab and Verizon, are reaping significant rewards. EcoLab, a global sustainability provider, has trained GenAI on clients’ operational and financial data to quickly and effectively identify the best resources for them, reducing the cost of time and resources. This proves that companies who have already adopted the technology across their operations are seeing benefits such as democratised data access, the ability to deliver actionable insights rapidly and monitor the benefits which have the ability to transform the company. Through being able to leverage, analyse and make data-driven decisions quicker and more effectively through GenAI, employees can prioritise other operations, which accelerates a company’s growth and enables them to scale quicker.

As well as reporting operational benefits, companies are seeing a measurable return on investment with GenAI, reaffirming the technology as both a financial asset and a key competitive differentiator. For example, Verizon—the telecoms giant—has developed a “centre of excellence” which allows them to monitor the ROI they are receiving for GenAI, meaning they can constantly monitor the financial benefits they’re receiving from the technology, and where it’s proving to be most beneficial. When investments are made, it is important to show the value and return making it suitable for the bottom line.

Democratised data access for decision making across levels of a business enables businesses to grow, scale and become more efficient.  This was highlighted in a recent report by MIT sponsored by ThoughtSpot found that nearly half of adopters of GenAI for analytics anticipate a 100% or greater ROI within three years. By moving away from a centralised framework, businesses enhance accessibility to data, and improve performance of data-driven decisions, which is beneficial for businesses in the long-run.

It’s a fact that innovation and originality is also crucial to empower and drive businesses towards efficiency and growth. GenAI for data analytics plays an important role in business innovation as through extracting insights from multiple datasets, GenAI can build a complete and personalise of different customers’ behaviour and habits in an instant. When using traditional in-house teams, although they may be able to reach the same conclusion, they may struggle to do it as quickly. Whereas harnessing GenAI for data analytics means results are achieved quicker, and therefore more can be achieved each day.

In the same way that GenAI has been widely adopted across businesses, agentic AI is now rapidly making inroads into businesses, and already transforming everyday operations. Agentic AI is offering businesses a step beyond GenAI—through operating autonomously to perform tasks in a human-like way. Agentic AI uses large language models (LLMs) to manage multiple agents, which can handle a vast range of operations from data search and analysis to driving complex data-led decisions. The technology’s systems go beyond when it comes to automating end-to-end processes, reducing manual effort and increasing efficiency across operations, to the point where they are widely described as being human-like.

Just as companies have been integrating GenAI products, more companies are now beginning to integrate agentic AI products into their ecosystems. Autonomous agents, such as Spotter, are allowing businesses to work with data in ways that hadn’t been previously possible – allowing them to converse with the system in the same way they would a human data analyst. By embedding the products into their existing business applications, when users ask questions of their data, they can now get the structured and efficient answers they need, which are adapted to both the industry and persona of its users.

To unlock transformative business value, companies must integrate GenAI and agentic AI without delay. Staying ahead of the curve ensures they dismantle bottlenecks, achieve rapid, data-driven insights, and enjoy substantial ROI—essential advantages in an AI-powered future.

The post From assistance to agency: how GenAI for analytics is unlocking measurable business value appeared first on TechInformed.

The UK government has been criticised by campaigners for creative industries after it proposed letting AI companies train their models on copyrighted works.

The proposal, which suggests that AI firms should freely leverage a new copyright exemption while training their algorithms, is “entirely untested and unevidenced” said crossbench peer Beeban Kidron, who campaigns to protect artist and creative rights.

Singer and songwriter Sir Paul McCartney warned AI could “just take over” if the firms writing LLMs are allowed to ignore copyright, but the government warned “legal uncertainty is undermining investment in and adoption of AI technology.”

Read more

Munich Airport aims to boost data use and cut wait times with AIRHART deployment

Munich Airport has unveiled plans for the next stage of its digital transformation after agreeing on a deal to implement the AIRHART data platform.

AIRHART, which is already in operation at Copenhagen Airport, uses real-time data analytics to improve the flow of passengers as they travel through an airport. It uses AI to optimise landing gates, predict bottlenecks and tie together all the different datasets and systems used in an airport.

AIRHART was created by Danish tech firm Netcompany in partnership with Copenhagen Airport and was deployed last year.

Munich Airport is Europe’s tenth busiest airport with over 50 million passengers a year.

“Munich Airport has a strong commitment to innovation and creating a seamless experience for the millions of passengers who visit and transfer at our hub. The implementation of AIRHART and our partnership with Netcompany is a significant step towards that objective,” says Florian Lesch, Senior Vice President IT at Munich Airport.

Read all about how it transformed the Danish airport’s operations

BlackBerry sells endpoint security arm Cylance to Arctic Wolf in huge loss

BlackBerry has reached a $160 million deal to sell Cylance to Arctic Wolf six years after it bought the endpoint detection and response vendor for $1.4 billion.

Arctic Wolf said the acquisition of the AI-powered cyber firm will bolster its EDR offerings, subject to closure of the deal which is expected to come in BlackBerry’s fourth fiscal quarter.

BlackBerry’s acquisition of Cylance in 2018 marked a significant step for the Canadian firm as it pivoted away from being a device manufacturer to focus on enterprise solutions, including security. It was BlackBerry’s largest ever acquisition at the time.

Arctic Wolf will pay $80 million once the deal closes, $40 million around a year later, and chip in 5.5 million shares too.

“Security has an operations and effectiveness problem and endpoint solutions alone have failed to live up to the outcomes they have promised for years,” said Nick Schneider, president and chief executive officer, Arctic Wolf.

“By incorporating Cylance’s endpoint security capabilities into our open-XDR Aurora platform, we will be addressing a rampant need for a truly unified, effective security operations that delivers better outcomes for customers. We believe we will be able to rapidly eliminate alert fatigue, reduce total risk exposure, and help customers unlock further value with our warranty and insurability programs.”

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ChatGPT search made available for all users

OpenAI is making ChatGPT’s search engine function available for all users, including an optimised version for mobile.

The generative AI platform first launched a search function back in October, but it was initially only available for paid subscribers. However, OpenAI revealed as part of its “12 days of ship-mas” the function will unlock for free tiers of ChatGPT from today.

On mobile, the search function will appear more like a traditional search engine, including answers more relevant based on location data.

Another feature aims to make ChatGPT search faster when you’re looking for certain sites, such as “hotel booking websites.” Now, ChatGPT will surface links to websites before taking the time to provide more information about each option.

Additionally, the AI can also automatically provide up-to-date information from the web when using Advanced Voice Mode, though that remains only available to paid users.

Read more

The post UK mulls copyright exemption for AI and BlackBerry incurs loss on Cylance sale appeared first on TechInformed.

Over the past few months, we’ve gathered insightful clips from various tech voices, answering one poignant question: “What are your 2025 tech trend predictions?”

We cover the direction of AI applications, green tech and sustainability developments, payment solutions, HealthTech advancements, the pervasive threats of cybersecurity, and more.

Watch here to find out which predictions from last year came true; TI:TALKS — 2024 Tech Predictions

The post TI:TALKS — 2025 Tech Predictions appeared first on TechInformed.

Central to its success is the personalisation offered by its Lifestyle Manager service, a digital assistant supported by Salesforce technology.

“To understand the motivations and passions of thousands of members globally, we need a flexible customer service platform that caters to both our business and client needs,” says Cathrine Levandowski, global head of operations at Quintessentially.

Speaking at Salesforce’s Dreamforce conference in San Francisco, Levandowski highlighted how Salesforce Customer 360 has transformed the company’s delivery of personalisation.

Tailor-made service

Quintessentially operates in 35 offices worldwide, communicating with members in 51 languages and representing 59 nationalities.

With such a diverse and demanding client base, the company manages over 300,000 member requests annually, using Salesforce Service Cloud to streamline communication across multiple channels, including email, phone, and WhatsApp.

Levandowski says Quintessentially’s ability to tailor services precisely is what sets it apart.

Lifestyle Managers collect and act on extensive client data, including travel preferences, memorable dates, and even favourite cuisines.

However, a significant challenge lies in coordinating communications, which often involve multiple contacts, such as executive assistants, personal assistants, and family members.

Previously, this was managed manually through Outlook, a process that Levandowski admits lacked the sophistication needed to track engagement or refine services.

Salesforce launches its first AI centre and accelerates with Aston Martin

Salesforce’s Distributed Marketing feature addressed this by enabling Lifestyle Manager to personalise emails for individual members and their networks, ensuring each recipient received relevant and timely information.

“Lifestyle Manager can now tailor communications beyond just the account holder,” explains Levandowski.

“For example, if I know a member’s wife loves fashion, I can send her curated recommendations. Before, we couldn’t track engagement or insights, but now we’re proactive and precise. That’s the luxury we sell.”

This improvement in communication enhanced the customer experience and enabled Lifestyle Manager to deliver Quintessentially’s unique value proposition more effectively, reducing errors and strengthening the company’s bespoke service offering.

Driving performance

According to Levandowski, the integration of Salesforce tools has had a tangible impact on Quintessentially’s business performance.

Using Marketing Cloud, she says that the company has been able to personalise, automate, and produce dynamic content tailored to individual members’ interests.

This enhanced approach to engagement increased newsletter open rates from 30% to 37%, significantly outperforming industry benchmarks.

This deeper level of connection with its members has translated into broader business success.

In 2023, Quintessentially reported a 30% increase in annual group revenue, driven by stronger member retention and satisfaction.

Concierge memberships grew by 40%, while member loyalty and feedback scores improved by 12%.

These results underscore the value of personalisation as a cornerstone of the company’s luxury services.

Quintessentially also expanded its operations in the US — a strategic goal for the business.

Membership in the US market increased by 40%, making it the company’s second-largest market after the UK.

Quintessentially credits Salesforce with playing a pivotal role in supporting this growth, providing the tools needed to scale operations without compromising on the high level of personalisation that clients expect.

Securing trust

Given the sensitivity of the data Quintessentially handles, security is a top priority for the company.

High-net-worth individuals entrust the firm with personal information, making it an attractive target for cybercriminals.

To address these concerns, Quintessentially relies on Salesforce’s compliance with PCI DSS standards, which set strict requirements for protecting cardholder data and preventing breaches.

“Salesforce provides the security we need,” Levandowski says. “That’s always been a priority for us.”

She adds that by aligning its operations with Salesforce’s robust security features, Quintessentially protects client data and reinforces trust, a critical factor in retaining and attracting members in this exclusive market.

Bespoke excellence

From better data insights to tailored communications, Quintessentially affirms that the Salesforce partnership has delivered its promise to provide members with a truly luxury service, proving that technology and personalisation can go hand in hand.

Read more: Agentic vs copilots: what’s the future of GenAI?

The post The digital butler: how a high-end concierge service is enhancing CX for its members appeared first on TechInformed.

According to the UK Business Data Survey, while nearly all the companies surveyed report handling digitised data, only just over 20% actively analyse it for new insights or knowledge. Of that group, only a third say this leads to innovation or the creation of new business functions.

Behind the scenes, experts highlight that most companies still face significant challenges in turning raw data into valuable insights.

While data is abundant, it is often fragmented, inconsistently structured, and of variable quality. Many companies have yet to define clear strategies for its use.

The promise of data extends beyond merely informing AI capabilities; it drives innovations such as digital twins, which improve operational efficiency, reduce carbon emissions, and enhance preparedness for cyberattacks. Yet, many businesses still struggle with harnessing the potential of this resource.

Unstructured Data

“One of the biggest challenges right now is that companies have so much data—structured, semi-structured, and unstructured—that it can be overwhelming,” says Vishal Marria, CEO of UK-based data management firm Quantexa.

Marcin Figurski, technical director at Google Cloud consultancy Qodea, echoes this sentiment, noting that fragmentation and data quality are ongoing issues.

“Another challenge is getting the right people to handle the data properly. It’s easy to gather data, but not easy to organise and use it effectively,” he explains.

He adds that many companies simply store data without categorising or structuring it, often with the vague hope that it might be useful later.

“But this approach doesn’t lead to actionable insights,” Figurski says.

“The problem is that they didn’t even know what data they had,” Figurski adds, highlighting the complexity created by a “shadow IT” environment in which different departments hoard and handle data independently, often without a centralised governance framework.

“There’s a lot of hype around ‘every company should be a data-driven company.’ But people assume that simply collecting data will lead to valuable insights. That’s not the case. The challenge is understanding the purpose of data, structuring it properly, and knowing how to use it effectively,” says Figurski.

Chris Harris, VP of field engineering at database platform vendor Couchbase concurs, pointing out that most businesses are sitting on vast, untapped data resources without the means to extract their full value.

“It’s like sitting on a gold mine without any shovels,” he says.

Without addressing these issues, Harris warns, companies risk falling behind in an AI-driven landscape. He adds that most organisations currently lack a suitable data strategy for generative AI, and only a fraction have implemented the necessary tools for advanced AI applications.

“The path forward requires strategic investment in robust data strategies, including infrastructure, skills, and culture. This isn’t about merely keeping pace—it’s about setting the stage for innovation in an increasingly data-centric business world,” he argues.

Solutions

Reflecting on the past year, Marria notes that many companies started running pilots and proofs-of-concept when generative AI became a hot topic, but the fundamental challenge always came back to data: “How to make it accessible, contextualised, and trustworthy—this is where many pilots faltered,” he says.

“The key to success is curating data properly so that it can be used effectively with AI.”

Harris adds that business data must be well-organised, seamlessly integrated, and readily accessible. “It needs to be accurate, consistent, and compliant with regulatory requirements. Achieving this level of data management requires organisations to carefully balance data acquisition, storage, and processing methods.”

“Establishing this solid data foundation is essential not only for generating meaningful insights but also for enabling modern applications that rely on data,” he concludes.

Data-driven results

For Quantexa, helping organisations manage their data has led to significant outcomes, such as improvements in fraud detection and customer experience.

One notable case was during the UK’s Covid-19 lockdowns, when the firm partnered with the UK Cabinet Office to support the ‘Bounce Back Loan Scheme’, designed to support small and midsize businesses by loaning between £2,000 and £50,000 at a low interest rate.

However, the government estimated that around 7.5% of its loans were fraudulent and needed a quick solution that could ingest more than 100 million data items and analyse it for dishonest behaviour.

“The key challenge was handling large datasets from multiple sources—external and internal data, and application data from various organisations—all without a common structure,” Marria explains.

The goal was to unify and contextualise the data, then apply predictive AI to detect anomalies, understand patterns, and drive action.

Similarly, Quantexa worked with telco giant Vodafone to optimise customer data management and improve customer service. “With the right data interpretation and AI, it becomes easier to identify customer issues, manage complaints, and better serve the customer,” says Marria.

The company also partnered with the bank, HSBC, where Marria notes, “it’s done a great job in getting their data in order. Now, we’re helping them take it to the next level by integrating LLMs with trusted, contextualised data and using knowledge graphs to drive deeper insights.”

Digital Twins

Meanwhile, Qodea’s Figurski argues that many companies are missing out on the potential of digital twins. “First, we’d need to understand the use case. What do they want to achieve with the digital twin? Is it forecasting, modelling, optimisation, or something else?” he explains.

Once the desired outcome is clear, the next step is identifying the data needed and how to access it. “After centralising the data into a system, we can begin to build a digital twin model based on the specific needs,” says Figurski.

From there, the process moves through proof of concept, testing, and eventual scaling into production.

Digital twins can be applied in a variety of ways. For instance, in cybersecurity, they allow companies to simulate attack paths and test their defence systems. In supply chain management, digital twins are used for predictive pricing—modelling the impact of geopolitical instability or climate change on supply chain disruptions.

“For example, businesses might use a digital twin to model and predict the impact of supply chain disruptions on prices,” Figurski explains.

In the realm of fleet optimisation, digital twins are helping companies model vehicle operations to reduce costs by improving driving behaviours, such as reducing harsh braking, optimising fuel efficiency, and refining delivery routes.

On the environmental front, digital twins are also being used to track and reduce carbon footprints. By simulating supply chain processes, businesses can measure the environmental impact of sourcing materials and assess their overall carbon emissions.

Unlocking an AI future

According to Marria, for organising the data AI is proving helpful.

“AI is a game-changer for intelligent data management. It allows organisations to make sense of their data in real-time, with full context—particularly valuable in regulated industries,” he says.

His firm also debuted its own GenAI tool, Q Assist, this summer that helps its customer’s teams get helpful insights into their data, backed up with Quantexa’s information base.

“The idea is that the LLM takes feedback, processes it, and integrates it with reliable data sources to create a meaningful interaction,” says Marria.

He adds that HSBC is using it to streamline analysis, reduce reliance on data science teams for ad-hoc data requests, and also support customer-facing teams with data insights.

Marria believes that companies using AI incrementally for efficiency alone risk missing the bigger picture.

“AI is about rethinking operations, not just speeding up old processes. It’s like transitioning from horse-drawn carriages to cars—you can’t just make the carriage faster; you need a completely new way of thinking.”

However, Couchbase’s Harris emphasises that AI may require a redesign of data architecture.

“Future-proofed organisations will need to consolidate platforms, eliminate silos, and create data systems that capture the ‘intelligence history’ of AI,” he says, highlighting the need for transparency and governance.

While AI offers immense promise, experts agree that its true potential can only be realised once organisations overcome the foundational data challenges.

As Marria concludes, “The next 10 years will be a transformative period, with many more use cases emerging and more benefits to be realised. But it’s going to require a lot of technical innovation to keep pace.”

Read more here: Shaping AI’s future: can the world agree on regulation?

The post Mastering data strategies for AI appeared first on TechInformed.

Digital technology consultancy Scrumconnect and public sector IT provider Aire Logic are the recipients of the two-year contract.

Both companies will work alongside the Department for Education’s Operations Infrastructure Group and support its software developers, testers, architects and DevOps staff to design, build, maintain and run digital services, enabling schools and education authorities to access DfE support services more easily.

The projects, which will support the government’s most recent budget pledge to spend £1.4bn of capital investment in the renovation and modernisation of schools across the UK, will focus on four key initiatives.

These initiatives are focussed on procurement; school technology services; a digital data hub called Schools Account as well as improvements to UK schools’ physical infrastructure and construction.

More access to data

A second two-year project worth £3.1 million will see Scrumconnect and Aire Logic working with the DfE’s Advanced Analytics Division to develop its Modernising our Reporting Environment (MORE) programme.

The initiative aims to make the sharing of data more efficient for education institutions. This will see existing infrastructure and platforms migrated to the cloud, and a new self-service data tool that will be built from scratch.

Initiatives within this project include the DfE’s data warehouse migrated to Microsoft Azure, to help make future updates and integrations more efficient.

The two firms will also modernise the government’s educational data platforms to help education institutions’ reporting and decision-making in areas such as school attendance as well as modernising the platform so that it can run on Microsoft Azure.

This, claimed the two firms in a statement, would help to improve collaboration and the sharing of data.

The contracted companies will also provide a new ‘self-service data query’ tool to help users pull data from the Further Education Data Warehouse.

The DfE said that the tool will be based on the detailed analysis of user requirements and will use data science to drive decision-making.

“It’s vital that education institutions have the tools to make effective data-led decisions,” said Mark Duncan, chief digital officer at Scrumconnect Consulting.

“We’re excited to be partnering with Aire Logic to bring our expertise in user centred design to these important DfE projects. This will enable DfE to build better digital services and user journeys and put vital data in the hands of education professionals.”

“Supporting education in the UK through technology solutions is an increasingly critical part of both the Government’s and our own mission,” said Joe Waller, co-founder at Aire Logic.

“As two like-minded companies with a history of success in modernising the public sector, we’re perfectly positioned to deliver solutions that match the Government’s ambitions around innovation and creating digital services that deliver in the long-term,” he added.

The post DfE awards Scrumconnect and Aire Logic £19m digital maturity & data contracts appeared first on TechInformed.

For the patient, this means prolonged call times, high volumes of repeat calls and heightened anxiety whilst they wait for a response.

What’s more, the disconnect between different systems, Trusts and other organisations involved in the healthcare journey (such as social care), continues to drive inefficiency and unnecessary waste. All too often we are seeing patients not attending appointments due to ineffective communication and not turning up, or patient transport still turning up when an appointment has been cancelled.

Events such as these are not only costing the NHS financially and in terms of resource, but it is also having a damaging impact on the patient experience, and ultimately – patient outcome.

Breaking the cycle

Over time a vicious cycle of inconvenience and inefficiency has been created, leaving patients feeling frustrated by having to wait to have their enquiries resolved. Often, additional stress is placed on service centre agents who are facing the brunt of this. Patients are frequently passed around in the process fuelling this frustration further, whilst other requests end up in an operational black hole – remaining unresolved.

So, what is the answer?

By bringing all relevant sources of patient data together into one single view, NHS Trusts and their service centre agents can be equipped with the information they need to transform experience and efficiency within the NHS.

Known as a Patient Relationship Management (PRM) system, solutions of this kind present the appropriate patient information in a meaningful way to assist with outpatient administration.

Faster access to information means better response times, and a better experience for both patients and NHS staff, offering an opportunity to break the vicious cycle of patient frustration, stress for agents and operational inefficiencies.

One view to rule them all

Having an immediate contextually relevant view of the patient when receiving an inbound enquiry can save 60 or more seconds per call – a significant time saving for outpatient service centres grappling with the waiting list backlog.

This will not only create additional capacity in service centres but can also provide a consolidation opportunity to support further service improvement and transformation initiatives in the future.

Having the right knowledge in the right place at the right time can enable better in-call decision-making meaning that outcomes and solutions can be reached quicker and easier – removing the need for follow-up calls and providing relief in what can often be a stressful scenario.

It can also support the identification and eradication of operational bottlenecks and inefficiencies caused by gaps in information and communication – such as follow-up appointments not being cancelled if the original appointment or diagnostics has not taken place. Every day a growing number of appointments are going ahead unnecessarily, wasting both consultant and patient time.

Forming a more holistic view of the patient can also ensure better attendance rates for appointments that are necessary. This can be achieved by taking a closer look at patient demographics and being aware of personal situations when arranging/setting appointments initially.

Insight into action

Knowledge is key when it comes to dealing with patient enquiries, however, there must also be workflows in place to turn that knowledge into action. Effectively configured workflows can enable follow-up tasks to be completed in just a few clicks, whilst the consolidation of these activities into a central view removes the need to rely on ad-hoc emails.

By adding this layer of structure, service agents – and patients – can be confident that next steps are followed up on and actioned in a timely manner.

That’s where PRM systems built via low-code platforms that easily integrate with other tools and technologies such as RPA can be particularly effective. Integration of this kind can allow the automation of onward tasks for further quality, performance and efficiency improvements.

Unlike traditional Enterprise CRM systems which require a long program of analysis, design, build and deployment, PRM systems built via low-code platforms, that accelerate development, can deliver immediate benefits as well as long-term improvements.

A streamlined future

With patient referrals continuing to run significantly higher than pre-pandemic levels, the intense pressure felt by NHS service centres is unlikely to slow down anytime soon. Especially given that the NHS’s Elective Recovery Priorities focus on better patient engagement and re-focusing capacity toward new patients.

This will certainly have an impact on the agents operating on the frontline – many of whom are already at risk of burnout and dissatisfaction. Equipping these agents with the right tools and platforms to work smarter and more successfully, therefore, must be a priority.

The same can be said for patient experience, despite efforts to reduce current NHS waiting list, it is likely to be a reality we will live in for some time. Focus should be placed on ensuring that patients are waiting well, and that when they reach out they are left reassured, rather than being faced with additional stress as a result of broken and disconnected systems.

NHS Trusts must work towards a streamlined future focused on improving the patient and employee experience. Technology will act as the foundation of this future, with PRM systems at the very heart.

Read more here: Postcards from the edge: NHS tech challenges and how industry can help

The post Can Patient Relationship Management platforms transform the NHS? appeared first on TechInformed.

The watchdog and consumer reports publisher advised consumers to research their next electronics purchases carefully after finding evidence of “excessive smart device surveillance” from Chinese air fryers and other products.

Which? claimed that smart air fryers from Xiaomi, Cosori, and Aigostar all wanted to know customers’ precise locations, as well as permission to record audio on the user’s phone.

The report claimed that the Xiaomi app linked to the smart device also connected to ad trackers from Facebook, TikTok’s Pangle ad network, and Tencent, depending on the location of the user.

It also said that Aigostar wanted to know the gender and date of birth of the owner when setting up an owner account and that both it and Xiaomi sent personal user data back to servers in China.

In the UK the Information Commissioner’s Office (ICO)  is due to publish new guidance for smart product manufacturers in Spring 2025.

This guidance must include clear advice on how consumers’ data can be used and the transparency required of businesses.

However, Which? added that it was concerned that manufacturers based abroad could take advantage of the challenges of enforcing compliance with guidelines.

Adam Brown, managing security consultant at Black Duck noted that the Cyber Resilience Act, which came into play this year, enforces stricter cybersecurity standards for all products with digital features sold in the EU requires manufacturers to implement mandatory cybersecurity measures throughout a connected product’s lifecycle.

However, he added: “‘Excessive smart device surveillance’ may not fall within the requirements of the CRA. Bringing connected devices into your home network opens doors for potential surveillance activity. And while an individual may not be a target for control or surveillance, as a part of a larger group, they may be.”

The post Air fryers may be secretly sizzling data, consumer group warns appeared first on TechInformed.

A CrowdStrike executive has told US lawmakers the company was “deeply sorry” for the global outage that grounded flights and left millions unable to work.

SVP of counter adversary Adam Meyers appeared before a US congressional committee to answer questions on the faulty software update that left millions of PCs disabled on July 19.

Lawmakers on the House of Representatives cybersecurity subcommittee pressed Meyers on how it occurred in the first place.

“A global IT outage that impacts every sector of the economy is a catastrophe that we would expect to see in a movie,” said Mark Green, chairman of the House Homeland Security Committee, in his opening remarks.

Meyers described the outage as a result of a “perfect storm” that was “due to a mistake”, adding that the cybersecurity firm is “determined to prevent it from happening again”.

Mr Meyers said the company would continue to act on and share “lessons learned” from the incident to ensure it would not happen again.

Read more…

LinkedIn ditches UK data for AI training over regulator concerns

LinkedIn will cease using UK data to train its artificial intelligence models after the Information Commissioners Office raised concerns.

The Microsoft-owned platform admitted it had trained its AI using UK user data without seeking their explicit consent as part of an updated privacy policy that went into effect on September 18, 2024.

This prompted concerns from the regulator, ICO, who welcomed the latest announcement from LinkedIn, saying it would work with the company to develop its approach.

Stephen Almond, ICO executive director regulatory risk, said: “We are pleased that LinkedIn has reflected on the concerns we raised about its approach to training generative AI models with information relating to its UK users. We welcome LinkedIn’s confirmation that it has suspended such model training pending further engagement with the ICO.

“In order to get the most out of generative AI and the opportunities it brings, it is crucial that the public can trust that their privacy rights will be respected from the outset.”

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FTX’s Ellison given two-year jail term for fraud

Former FTX executive Caroline Ellison has been sentenced to two years in prison for her role in the collapse of the currency exchange.

Ellison joins former partner Sam Bankman-Fried among those convicted over FTX’s collapse, which has been called one of the biggest financial frauds in cryptocurrency history.

Ellison accepted a plea deal that saw her admit to charges including wire fraud and money laundering. She also testified against Bankman-Fried, who has already been sentenced to 25 years in prison for stealing more than $8bn (£6.3bn) from customers.

Under the plea deal, Ellison has also agreed to forfeit more than $11bn (£8.2bn) to the court.

Apologising in court, she said: “On some level, my brain can’t even comprehend the scale of the harm that I caused.”

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ChatGPT-founder Sam Altman outlines “superintelligence” timeline

We are as little as eight years away from the creation of artificial general intelligence, according to OpenAI CEO Sam Altman.

AGI, which Altman refers to as “superintelligence” in a recent essay, is a computer that can reason as well as or better than humans.

“It is possible that we will have superintelligence in a few thousand days; it may take longer, but I’m confident we’ll get there,” he wrote in the essay titled The Intelligence Age.

Altman, who helped build ChatGPT and usher in the latest generation of generative AI, used the 1,100-word essay to make a case for giving as many people as possible access to AI to facilitate a leap in human prosperity.

“In the future, everyone’s lives can be better than anyone’s life is now. Prosperity alone doesn’t necessarily make people happy. There are plenty of miserable rich people, but it would meaningfully improve the lives of people around the world.”

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James Cameron joins board of AI startup

Hollywood director James Cameron has joined the board of UK-based AI startup Stability.

The Academy Award-winning director, famed for future-looking blockbusters including the Terminator series and Avatar, said he was interested in the intersection of CGI and GenAI in image creation.

Stability is the company behind the AI image model Stable Diffusion, which, alongside Midjourney, helped capture the initial mainstream interest in GenAI several months before ChatGPT’s release.

Cameron said: “The convergence of these two totally different engines of creation will unlock new ways for artists to tell stories in ways we could have never imagined.

“Stability AI is poised to lead this transformation. I’m delighted to collaborate with Sean, Prem, and the Stability AI team as they shape the future of all visual media.”

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