Latest news with #ChiefDigitalOfficer
BBC News
31-07-2025
- Health
- BBC News
Humber region hospitals allow online booking of appointments
A service has been launched to allow people to book and manage their hospital appointments and tests Patient Portal run by NHS Humber Health Partnership will give patients the power to log in and select appointment dates and times, without needing to wait on the telephone.A partnership spokesperson said people will still be able to manage their appointments via phone if they prefer. The service will be piloted in Hull before being expanded into Goole and northern Lincolnshire. Chief digital officer at the partnership Andy Haywood said it would bring hospital services "in line with what we expect in every other aspect of our daily lives"."Our new patient-led booking service will transform the way in which our patients interact with their care," he said."This new service will see an end to patients receiving a letter with an appointment they can't make and then having to wait long periods on the phone to try and rebook."The system will also send messages if needed, such as informing patients of a change in location of an appointment, or if an earlier slot becomes can also check whether a patient is able to attend, allowing appointments to be given to somebody else if not to highlights from Hull and East Yorkshire on BBC Sounds, watch the latest episode of Look North or tell us about a story you think we should be covering here. Download the BBC News app from the App Store for iPhone and iPad or Google Play for Android devices.
Bloomberg
23-07-2025
- Business
- Bloomberg
Adani Pulls Back From Super App Plan as Losses Mount, Fires Executives
The Adani Group has shelved its plans to build a consumer-facing super app after incurring significant losses and internal turmoil, people familiar with the matter said, marking a retreat from its ambitions to build ' the Ferrari of the digital world.' The Indian conglomerate folded its standalone digital unit, Adani One, into its airport holdings division earlier this year, the people said, asking not to be identified discussing private information. Chief Digital Officer Nitin Sethi, who was overseeing the unit, along with several employees have left the organization amid an internal probe into mismanagement of the business, they said.
Forbes
16-07-2025
- Business
- Forbes
The Invisible Revolution: Why Operating Models Must Shift In The Age Of AI
Calvin Goulding, Chief Digital Officer at G8 Education | Building what matters—where purpose, people and performance intersect. We're at a fascinating and often uncomfortable inflection point. Not because AI is knocking on the door but because it's already in the room, quietly reshaping how work gets done in ways that are easy to miss unless you're paying close attention. As someone deeply fascinated by how progressive companies adapt and thrive, I've spent years closely tracking the quiet revolution happening beneath the surface. The most progressive organizations already operate with models built for speed, adaptability and distributed decision-making. Their operating models are naturally positioned to absorb, adapt to and scale with the extraordinary pace of the AI revolution. This puts them in a position to maximize the value creation of AI, thereby furthering the gap between themselves and their competitors. But AI won't just fit into the current model; it will continue to reshape it. That's the deeper shift underway. This is about reimagining how decisions are made, how teams function and how value is created, fundamentally and continuously. Let's explore what that looks like in the real world. 1. Hierarchies are giving way to smarter, faster networks. Let's be honest—traditional hierarchies weren't built for speed. But AI thrives on access, speed and experimentation. It doesn't care about job titles. Take Amazon, for example. Everyone loves the 'two‑pizza team' story, but the real magic is in how those small teams move: fast, data‑fed and empowered. There's no waiting for steering committees to approve the obvious. Unilever is going a similar route with digital hubs embedded globally, putting insights and decision rights closer to where value is created. Less central command, more local velocity. Unilever 'has created an industry‑leading AI research hub and implemented over 500 AI projects across the globe' as part of reducing complexity and accelerating local decision‑making. Takeaway: Relying on command‑and‑control is a bottleneck. The game now is distributed intelligence and trust. 2. It's not humans or AI, it's humans with AI. We've seen this movie: Automation arrives, and people worry about being replaced. But the real wins are happening when humans and machines team up. JPMorgan Chase isn't just automating legal reviews for fun—it's freeing up analysts to do actual thinking, not page‑flipping. Their COIN system automates contract reviews, saving approximately 360,000 hours of manual effort annually. In healthcare, Mayo Clinic uses AI to do early triage, so doctors can focus on what only they can do. For instance, they implemented an AI‑based triage system in emergency departments (like STEMI detection) back in 2020. I've spoken with teams who thought adding AI meant layering a tool on top of existing processes. It didn't work—until they rethought the process itself. Takeaway: Stop grafting AI onto old workflows. Redesign the work, and partner with the machine. 3. Static departments can't keep up. Most organizational charts still look like they were drawn in the '80s, finance here, marketing there, HR off to the side. But AI and moden organisations don't respect those silos. Tesla is a wild example of this. It's not just building cars, it's reconfiguring around capabilities that stretch across software, manufacturing and energy. Its factories, energy units and software teams are tightly integrated, using AI across manufacturing and vehicle operations. Spotify ditched rigid functions in favor of squads and tribes. It's messy sometimes, sure. But it's also faster and more aligned with what their users actually do. The 'Spotify Model' explicitly uses autonomous squads within tribes to drive agility. Takeaway: Design for change. Build capabilities that can flex and move—not siloed functions that stay stuck. 4. Internal experience matters more than ever. Personalization used to mean targeting your customer. Now it means tailoring how your people work inside the business. ServiceNow, Salesforce—these companies are building tools that don't just serve the business but mold to each employee's context. ServiceNow's Now Platform delivers personalized workflows, self‑service and AI‑guided recommendations for employee journeys. Salesforce's Agentforce (and Career Connect tools) brings AI into employee-facing workflows—for example, real-time assistance inside Sales Cloud or career guidance integrated with Slack. Even Accenture is experimenting with digital twins and personalized dashboards so consultants aren't drowning in irrelevant data. Takeaway: Internal systems should adapt to your people, but this must be done with a pragmatic lens. The goal isn't personalization for its own sake but to thoughtfully balance human needs with efficiency, experience, quality and speed. Designing around people should be deliberate, data-informed and grounded in outcomes. 5. Culture still eats everything. You can buy tech. You can hire data scientists. But if your culture penalizes risk‑taking, hoards information or waits for 'perfect plans,' you'll stall. Adobe knew this when it bet the farm on subscriptions and embraced failure as part of the journey. DBS Bank built a culture modeled after tech giants—not just in buzzwords but in behaviors: autonomy, speed, customer obsession. Under CEO Piyush Gupta, DBS pivoted after a meeting with Alibaba's Jack Ma in 2014 and has since transformed into a global digital banking leader. Takeaway: You can't bolt AI onto a legacy mindset. Culture is the multiplier or the handbrake. Conclusion We're not talking about some future state. The operating model shift is already underway, and the gap between those who get it and those who don't is widening fast. This isn't just about technology. It's about reimagining how your organization works, adapts and delivers. The smartest leaders are not asking, 'What AI tool should we buy?' They're asking, 'What do we need to unlearn and evolve as a business?' Because that's where the real work begins Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Forbes
14-07-2025
- Business
- Forbes
Your Building Is Talking. Here's How To Listen With AI And Automation
Riaz Raihan is SVP & Chief Digital Officer at Trane Technologies. Why the big push toward digitization in the built environment? What aspects of a building have the most potential for positive operational and environmental impact? What does long-term value truly look like? In an era where buildings' energy management and cost efficiency are paramount, these questions are increasingly relevant. Rising energy rates and a significant shift from equipment and services-based needs to broader outcome-driven demand make finding answers crucial. Despite breakthrough innovation over the last several years, buildings still can't actually speak to us. They do, however, constantly give us non-verbal cues through technologies like AI and autonomous controls. These digitization solutions can significantly reduce buildings' operating costs and their carbon footprint. So, the question to ask is: Your building is talking, but do you know how to listen? The Discreet Cool Factor We've all heard how cool, cutting-edge technologies like AI and autonomous controls are enhancing productivity, efficiency and decision-making across nearly every sector. It's easy, and warranted, to get excited about them, especially in the built environment. As I've seen in my role as senior vice president and chief digital officer at Trane Technologies, AI and automation are being practically applied in HVAC systems to support outcome-based performance. And for good reason, as more than 50% of a building's operating cost can be attributed to its heating, ventilation and cooling. However, digital technologies require significant power to sustain and advance their capabilities, increasing strain on our grids and energy consumption. As such, we can't fall into the trap of implementing digital just because it's trendy. The true allure of digitization and AI in the built environment lies in their ability to deliver operational cost savings, emissions reductions and optimal performance, which I see as their most discreet cool factor. Interpreting Your Buildings' Non-Verbal Cues This is where your buildings' non-verbal cues and your ability to "listen" become critically important. Digitally enabled AI technologies like autonomous controls can help us look at both structured data (building layout, indoor temperatures, equipment specifications) and unstructured data (weather patterns and forecasts, pollution data, occupancy patterns) to optimize buildings' energy performance. As AI-enabled building controls learn how to respond to changing conditions, including energy pricing fluctuations, they can autonomously optimize energy performance and enable cost-effective predictive maintenance. I like to frame this in the context of streaming platforms, which regularly feed us new and interesting content, showcasing the value of our monthly subscriptions—so much so that we are often compelled to set them on auto-renew. But what happens when the content becomes stale? If you go weeks without anything new catching your eye, you start doubting its value, right? You might even cancel one subscription and opt for another. The same mindset can be true for the built environment, but that's also where digital enablement drives significant value—by reading and acting on a building's non-verbal cues. Technologies like digital twins, building automation systems and autonomous controls capture real-time data and advanced analytics—continuously optimizing system performance by enhancing efficiency and reducing energy consumption and operational costs. Leveraging these solutions can help you listen to and understand your buildings while enabling energy and cost savings, demonstrating their ROI and economic viability. In some cases, I've seen energy savings of 25% to 35% and paybacks of 12 to 18 months. Just like streaming platforms continue to feed us fresh and engaging content, proving the worth of their subscription fees, a building's digital technologies also deliver consistent, real-time value. Potential Challenges Turned Successful Outcomes Implementing these technologies requires a comprehensive approach. Additional factors, including data requirements, computing capabilities and internal skills must be considered. The availability of historical energy use data and operational data on a building's HVAC systems and other parameters is critical for identifying patterns and improvement areas. This is a key component of autonomous controls and building automation systems. Access to a building's architectural plans and layouts is also essential for creating accurate digital twins. A robust cloud infrastructure to process large volumes of data and reliable and secure communication protocols for data transmission and storage must also be factored in. But access to information is null if you forget the most important piece of the implementation puzzle: a skilled talent pipeline adept at analyzing data and machine learning techniques to derive actionable insights and reduce latency. While innovative digitization technologies are changing the game for reducing energy demand and emissions across the built environment, prioritizing the talent to advance them is vital. Of course, implementation can still come with challenges, including data integration and system interoperability. Integrating data from a variety of sources (sensors, historical records, occupancy and weather patterns) into a unified system can be complex and time-consuming. Different systems may also use varying formats, making it harder to standardize and harmonize data for analysis. But these potential challenges can be turned into successful outcomes. One important aspect is having a centralized platform capable of aggregating data into a single repository, where data is more easily accessed, managed and analyzed. Driving Demand-Based Outcomes The built environment has seen decades of trends and shifting perspectives from building owners and facility managers. Fifty years ago, the only thing customers cared about was the capital investment needed to install a high-quality HVAC system. Eventually, that progressed to high-quality and well-maintained systems, with good indoor air quality. Today, things look drastically different. Customers demand outcomes, not just equipment that meets their day-to-day heating and cooling needs. They require high-quality, well-maintained, smart and adaptable machines that help reduce emissions, cut costs and optimize energy consumption. This aggregation of behavioral change affirms the growing demand for purpose-driven, sustainable technology that drives energy efficiency and decarbonization. AI and digital technologies can leverage the things that your building and its environment are telling you to drive these outcomes, underscoring the importance of your ability to listen to your building when it's talking to you. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
