Historically, telcos were able to rely on providing voice and data connectivity to achieve revenue growth and consistent profit margins. However, since roughly the introduction of 3G cellular network technology and the first version of the Apple iPhone (circa 2007), third-party digital innovators have moved in to siphon off emerging monetization opportunities while curating vast developer ecosystems, relegating telcos to the connectivity provider role. Telcos have been struggling to take advantage of ever-faster networks, a growing diversity of devices, and massive popularity of social media and mobile video applications, while struggling to keep pace with ever more exacting network performance requirements, ever since.

With this backdrop, the meshing of 5G networks and API exposure can empower telcos to reinsert themselves as a key connectivity platform within the digital landscape by unlocking the ability to more easily sell and scale customized, programmable connectivity underpinned by app developer platforms grounded in telecom network APIs.

FIGURE 1: Network API Primary Segments

Telecom Ecosystem Evolution: Network API Market Makers/Drivers and Likely Roles

Telcos face several – non-exclusive – paths to market. As 5G service exposure invites a more vibrant telecommunications ecosystem, there are many stakeholders exploring how best to foster development of new API service bundle–fueled services that can generate new innovation and, by extension, new revenue from 5G service exposure. The core constituent groups are described in the sections that follow.

Telcos: Telcos already have the ability to expose network capabilities via an API gateway enabled by the Service Capability Exposure Function (SCEF) in 4G/LTE networks; or the Network Exposure Function (NEF) in 5G networks. Telcos also provide the underlying connectivity, which could be delivered via custom network slices, guided by API and policy definitions to align with developer needs. Developing services – utilizing CAMARA specifications and/or non-standardized APIs – alongside their existing connectivity business models will bring telcos more in line with cloud and edge service providers that focus on enabling third parties to build services on top of their infrastructure. This can lead to a deeper monetization of network infrastructure and increase network accessibility and commercial engagement with application developers.

Network Infrastructure Vendors: These vendors provide the underlying infrastructure (e.g., hardware and software) to enable the programmable 5G service. Further, vendors could conceivably end up helping build the service APIs as bundles and offer them as standalone or white-label solutions to comms SPs or platform providers alike. Vendors also stand to benefit from a robust 5G API ecosystem that can contribute to both increasing infrastructure sales required to deliver advanced connectivity services and offering them a new revenue stream. Nokia, Ericsson, and Oracle represent some of the vendors highlighting early activities in this area.

CPaaS Platforms/API Aggregation: Communications Platform as a Service (CPaaS) providers such as Vonage and Infobip players provide a known way to aggregate and consume APIs for a range of communications services, including customer engagement through multiple channels and two-factor authentication. CPaaS and API aggregators are a natural channel partner for network APIs, broadening developer market access to these services.

Hyperscalers: Hyperscale cloud providers (HCPs) provide a potential path for integrating network APIs via an API gateway and to integrate network performance capabilities enabled through these network APIs, along with cloud computing and storage, in order to build high-value applications in support of a number of vertical markets and use cases. HCPs all support enormous bases of cloud developers that are well-versed in API consumption and lifecycle management. HCPs are actively participating in industry initiatives such as CAMARA and the GSMA Open Gateway Alliance, and represent a significant potential opportunity.

Independent Software Vendors or Edge Platform Providers: Independent software vendors (ISVs) can design and bundle APIs for SaaS offerings to organizations, simplifying API consumption for organizations that lack the ability to embed APIs themselves. In addition, IDC observes an emerging subset of the app platform market that focuses on enabling edge applications (e.g., IoT edge apps) that are hosted and run across edge sites. Specific platforms may focus on discrete vertical opportunities to specialize. ISVs are able to specialize in respective verticals and use cases (e.g., industrial automation, healthcare, and entertainment), providing a logical route to drive network API adoption among enterprise and industrial adopters that would be most comfortable consuming new software offerings.

Education and Training are Keys to Growth

While the potential opportunity for network APIs is potentially limitless, the key to their success lies largely in the ability for network API proponents to articulate their value in these various contexts. In particularly, the largest opportunity may be in educating the developer community on what value network APIs can bring in augmenting enterprise and consumer-facing applications, what combination of network APIs can be brought to bear simultaneously to address various requirements pertaining to Quality on Demand (QoD), edge, security, location, and a number of other network capabilities enabled by APIs. IDC believes that industry groups such as CAMARA, Open Gateway Alliance, and TM Forum will need to devote as much of an effort to educating (and potentially certifying) app developers in network API capabilities and best practices, as it is currently devoting to establishing and proving out their technical capabilities.

For a deeper dive into these topics, watch IDC’s July 10th webinar, ‘Revenue Enablers for the Future Telco: APIs, AI, and Emerging Tech”.

In the dynamic and competitive landscape of B2B technology, gaining visibility and credibility can be a significant challenge for startups. While many focus on product development and customer acquisition, engaging with industry analysts is often overlooked.

Yet, building relationships with these influential figures can provide startups with critical insights, validation, and market presence. Let’s debunk some common myths that deter startups from engaging with analyst firms and explore why these relationships are invaluable.

Myth 1: Analysts Are Only For Large, Established Vendors

Many startups believe that analyst relations are reserved for large, established companies with extensive resources. However, this is far from the truth. Analysts are keen to discover innovative solutions and emerging players in the market.

Engaging with analysts early can help startups refine their value propositions and ensure a better product-market fit. Building these relationships early on can also lead to significant opportunities, such as mentions in influential reports and increased visibility within the industry.

Myth 2: Analysts Are Too Expensive

The cost of engaging with top-tier firms can indeed be high, often perceived as prohibitive for startups. However, the return on investment can far exceed the initial expense. Analysts provide invaluable insights that guide product development, marketing strategies, and overall business direction.

Additionally, startups can opt for strategic inquiries, briefings, and free resources to begin benefiting from analyst insights without committing to full subscriptions. Engaging with analysts can be more cost-effective than traditional PR efforts, offering substantial credibility and market presence.

That’s why IDC provides a cost-effective solution for startups and emerging tech vendors only. Startups can leverage IDC’s insights to better understand market trends and competitive dynamics. Engaging with IDC analysts can help startups position their products effectively and gain visibility among potential customers and investors.

Myth 3: Startups Don’t Need Analysts Until They’re Bigger

Some startups think they should wait until they are more established before engaging with analysts. In reality, early engagement is crucial. Analysts can provide early-stage feedback, helping startups avoid costly mistakes and better align their products with market needs.

Being on an analyst’s radar early can also lead to significant opportunities, such as mentions in reports and invitations to industry events, which can greatly enhance a startup’s visibility and trustworthiness.

Why Engage With Industry Analysts?

Influence and Credibility: Analysts are among the top influencers in the technology buying cycle. Their endorsements can significantly boost a startup’s credibility and market presence.

Market Insights: Analysts offer deep insights into market trends, customer needs, and competitive landscapes. These insights can inform strategic decisions and help startups stay ahead of the curve.

Go-to-Market Strategy: Analysts can validate go-to-market strategies, helping startups refine their messaging and positioning to better resonate with target audiences.

Investor Attraction: Positive analyst mentions can attract investor interest, making it easier to secure funding and partnerships. Investors often look for third-party validation when evaluating potential investments.

Time & Resource Efficiency: Engaging with analysts can save startups time and resources. Analysts aggregate and distill vast amounts of market data, providing actionable insights that startups might otherwise spend significant time and money gathering independently.

Best Practices for Engaging with Analysts

To maximize the benefits of engaging with industry analysts, it’s essential to approach the relationship strategically and thoughtfully. Here are some best practices that startups can follow to build and maintain effective analyst relations.

Identify Relevant Analysts: Research and identify analysts who cover your industry and technology space. Look for those who have influence over your target market.
Develop a Strategic Outreach Plan: Tailor your outreach to align with the analyst’s interests and expertise. Highlight your unique value proposition and how it addresses market needs.
Prepare Thoroughly: Create a compelling presentation that includes your company’s background, product roadmap, market differentiation, and customer success stories. Practice your pitch to ensure clarity and confidence.
Engage Consistently: Schedule regular briefings to keep analysts informed about your progress and developments. Maintain open communication and seek their feedback.
Leverage Analyst Endorsements: Use positive mentions and quotes from analysts in your marketing materials, sales pitches, and investor presentations. Highlight these endorsements to build credibility and attract attention.

Conclusion

Engaging with industry analysts is a strategic move that can provide tech startups with significant advantages. By debunking common myths and understanding the value that analysts bring, startups can leverage these relationships to enhance their market presence, credibility, and growth potential. Start early, engage consistently, and use analyst insights to drive your startup’s success.

If you’re ready to take your startup to the next level, don’t hesitate to reach out to industry analysts and start building these valuable relationships today.

For more details on how to start and maintain these valuable relationships, consider reaching out to one of our specialists to explore partnership opportunities.

“Key Highlights from the 2023 CIO Sentiment Survey” by Mona Liddell provides key insights to understanding the operational dynamics and strategic directions of IT organizations. In this blog, we’ll cover four that rise to the surface. Let’s dive in to some of them!

Firstly, let’s discuss Digital Transformation (DX). While integrated, continuous enterprise-wide DX strategies once took the spotlight, organizations are now leaning towards shorter-term approaches.

This shift may stem from factors like organizational learning curves, economic uncertainty, or the aftermath of global disruptions, such as the ongoing recovery from the pandemic. Figure 1 shows significant growth in organizations who have transformed or are integrated than over the previous year. Almost 65% were in the transformed or integrated maturity groups versus even a year previous where it was only 45% – an almost 45% increase.

Next on the agenda is Generative AI (GenAI), a topic sparking both excitement and caution. While about 32% of IT organizations have already adopted GenAI, a considerable number are still either not investing or only developing the use cases. This means these more conservative organizations are not developing the skills, building the data platforms, or examining the competitive advantages GenAI can provide.

IDC recommends piloting GenAI as a way to understand the potential business benefits, develop governance structures, and identify gaps within the organization to deliver its potential. Efforts can start with the simplest use cases, such as productivity, before expanding to functional and industry use cases.

GenAI isn’t a fad, like NFTs or the metaverse. It is a sea change on the level of the ’80s PC revolution and the ’00s smart phone transformation. A notable 22% of organizations are already adapting to the emergence of GenAI by actively changing their hiring plans. These companies may be creating new roles to leverage the early benefits of GenAI. 

Meanwhile, cybersecurity remains a perennial concern, with varying investment priorities across organizations of different sizes. Both midmarket and large enterprises struggle to recruit cybersecurity talent, akin to finding a needle in a haystack. Larger enterprises due to more resources are less affected by this cybersecurity skill gap, but still struggle.

The question organizations need to consider is whether creative solutions can help bridge the gap, like using GenAI tools to summarize security alerts for less experienced staff, retraining existing staff, implementing robust internship programs, machine learning, and moving from discrete applications to a platform approach to security to simplify security management.

Technical debt poses another challenge, with a majority of organizations failing to allocate adequate resources or establish formal processes for its management.

While a majority of organizations allocate a small portion (12.8% average) of their IT budget to reduce technical debt, a significant number (79%) do not have formal processes for tracking and reporting this debt.

This gap in tracking and reporting could affect the strategic planning and alignment of IT initiatives with business objectives. It also reflects a need for more structured reporting and management practices to ensure that technical debt is accounted for in executive decision-making. However, amidst these challenges, there’s a silver lining: widespread adoption of cloud-based solutions and virtualization as integral parts of digital transformation endeavors.

These insights prompt several recommendations:

Balance Short and Long-Term DX Strategies: Maintain equilibrium between short-term necessities and long-term digital roadmaps. Establish agile practices that allow for rapid adaptation between immediate market demands and long-term digital evolution to help ensure that short-term shifts don’t disrupt the broader business goals of the organization.
Develop a Strategic Approach to GenAI Adoption: Plan strategically, incorporating governance principles and adoption roadmaps. In anticipation of GenAI-driven market changes, proactively revise IT hiring strategies while also upskilling current employees to ensure alignment with the future demands of GenAI integration. 
Invest in Cybersecurity Talent: Prioritize recruiting and developing cybersecurity professionals. Prioritize investments in training programs (e.g., certifications and workshops) to upskill current employees in cybersecurity practices and incorporate an internship program for fostering new talent, thereby mitigating the talent shortage by internally growing cybersecurity skills and introducing fresh perspectives through internships.
Establish Formal Processes for Technical Debt Management: Implement structured processes for tracking and mitigating technical debt.. This should include regular audits of existing systems, quantification of debt, and documentation of remediation plans. Second, develop a prioritization framework to tackle technical debt, focusing on areas that yield the highest risk to the business or present opportunities for quick wins. A future tease is IDC will be releasing a methodology to assess technical debt in a report to be published in April 2024.

These insights, drawn from a global survey of IT leaders, provide valuable guidance. However, it’s essential to tailor strategies to fit individual organizational contexts and needs. The findings from this survey have been exclusively depicted in an eBook for technology leaders like you. Click the button below to download the eBook now.

Learn what matters most to your customers with IDC’s AI Use Case Discovery Tool—find out more.

High Expectations Collide with Market Realities

Telecom Service Providers are facing historic challenges amidst shifts in both enterprise and consumer demand and challenges transforming from “connectivity providers” to digital platform players.

Historically, telecom service providers have championed connectivity at scale. In past decades, this proved a profitable strategy, with the value of connectivity garnering consistent year-over-year revenue growth and profits. However, recent years have seen telecom providers grapple with a host of challenges including industry competition, commoditization of services, and inflexible IT systems that have made it hard for them to swiftly innovate and compete against new threats.

Further, while network traffic continues to rise, predominantly driven by video apps, service providers have been unable to effectively monetize this traffic growth. The disconnect between revenue growth and network traffic growth remains one of the top challenges globally for service providers as they hunt ways to reinsert themselves and justify connectivity as not just a commodity, but as a value-based service that can be delivered to support a range of use cases and verticals.

In response, many forward-thinking telecom providers have made a purposeful decision to focus their technology offerings and ecosystem partners on targeting digital engagement and new revenue opportunities and rearchitecting their technology stacks to align with hyperscale cloud models as a means to simultaneously control costs and position for service agility longer term.

Even so, third-party entities, including CPaaS, cloud, and other digital platform players, have moved into largely siphon off these digital opportunities while curating vast developer ecosystems, once again relegating many telecom providers to a connectivity-only role.

New Tools in the Arsenal Create New Monetization Opportunities for Telcos

Amidst this push and pull of telecom service provider efforts, a new opportunity has emerged, driven by the promise of SA 5G networks and API exposure capabilities to empower telecom providers to reinsert themselves within the digital landscape by unlocking the ability to more easily sell and scale customized, programmable connectivity designed to be packaged and consumed by application developers.

Unsurprisingly, hyperscale cloud providers, CPaaS companies, and systems integrators have also positioned themselves for this new market opportunity by aligning with industry consortia (e.g., Camara, Open API Gateway) that are championing global standards; however, it remains to be seen where, how, and by whom value will ultimately be created and monetized.

Figure 1: Emerging Telecom and Network API Ecosystem

As part of these market developments, the worldwide IDC team has spent the past couple of years building a methodology to size this opportunity and define ways the telecom API ecosystem can work together to enhance this emerging market.

Telecom Service Providers Can Capitalize on AI and GenAI to Improve Business Results and Potentially Reshape Their Market Role

While APIs represent one-way service providers can capture new monetization opportunities, Artificial Intelligence (AI) presents another avenue to drive business results. More specifically, AI can be inserted into the telecom technology stack to improve TCO, enhance service agility (e.g., AIOps), as well as improve the customer experience (CX) lifecycle.

As telcos move toward future network architectures governed by cloud-native architectures, this ushers in a much greater role for automation and orchestration across various physical, virtual, and containerized network functions, as well as AI-informed operations and monetization platforms.

This in turn raises the importance of adopting AIOps within network operations; however, network-related AIOps brings its own unique set of challenges for Telecom Service Providers as well as a vendor community that overlaps but does not entirely match, the more generalized ITOps vendor roster.

Meanwhile, GenAI has emerged as a powerful tool to enable telcos to embrace some of the benefits of AI while simultaneously investing in the internal skillsets and capabilities required to embrace AI more broadly. The graphic below highlights some of the key use cases IDC envisions for GenAI across telco environments.

Figure 2: GenAI Telco Use Cases Across Telco Environments

While this graphic provides an optimistic outlook for the full set of Gen AI’s impact on telecom service providers, the reality is it will take time, effort, and AI partners for telecom providers to realize gains from AI. Indeed, with AI curators racing to drive AI innovation across multiple environments (e.g., hybrid and multi-cloud, etc.), it is likely multiple models will become prevalent in which telecom service providers serve dual purpose by becoming some of the strongest consumers and distributors of AI and Gen AI going forward.

Further, interest in AI applications is also prompting service providers to build near-term roadmaps clarifying how enterprise customers can leverage their core and edge assets to support emerging use cases (e.g., AI inferencing at the edge) while reinforcing connectivity as the foundation of AI-enabled applications and services. Indeed, while AI is being emphasized by many organizations, it will require a global distribution mechanism to help scale. Hyperscale cloud providers are top-of-mind, but telecom service providers can also play a role in connecting AI apps.

Overall, it is a critical time for telecom providers, and their technology vendors, to synchronize on key priorities and investment strategies, particularly in light of historical struggles to optimally monetize telecom networks. Doing so can enable them to rearchitect a brighter future for telecom monetization and set them up for a key role in a digital, AI-centric world.

For a deeper dive into these topics, watch IDC’s July 10th webinar, “Revenue Enablers for the Future Telco: APIs, AI, and Emerging Tech”.

In today’s high-stakes sales environment, managers are grappling with an array of challenges that can stifle growth and efficiency. From the daunting task of managing diverse teams and complex sales processes to the relentless pressure of meeting ambitious targets, the role of a sales manager has never been more demanding. Add to this the reality of having to do more with less—facing static staffing budgets amidst increasing operational complexities—and it’s clear that the traditional approaches to sales management are no longer sufficient.

Enter Artificial Intelligence (AI). This transformative technology is not just a buzzword, but a practical solution poised to revolutionize sales management. AI’s ability to automate administrative tasks, provide personalized training, and deliver data-driven insights offers a beacon of hope for overwhelmed sales managers.

By harnessing AI, sales leaders can not only navigate the challenges of their roles more effectively but also unlock new levels of productivity and strategic decision-making. This introduction to AI in sales management marks the beginning of a new era, where efficiency and growth go hand in hand, empowering managers to lead their teams to unprecedented success.

The Challenges Sales Managers Face

In today’s high-pressure sales environments, sales managers are grappling with a myriad of challenges that test their limits daily. The transition from top-performing salesperson to a managerial role often comes with the assumption that success in sales equates to success in leadership. However, the reality is far more complex. Sales managers find themselves overwhelmed by the immense workload, which includes not just leading and motivating their teams but also handling administrative duties and striving to meet ambitious sales targets.

The scarcity of resources, be it time, budget, or staffing, further exacerbates the pressure on sales managers. They are also tasked with navigating the intricate sales processes and managing a deluge of data from various sources without adequate analytical tools. The diversity within teams, in terms of skill sets, personalities, and working styles, adds another layer of complexity to ensuring cohesion and productivity. Continuous learning and development for both the managers and their teams are essential to maintain consistency and adherence to sales methodologies, all while under relentless pressure to achieve organizational goals.

Despite these challenges, organizations often expect sales managers to do more with less. With staffing budgets remaining stagnant and the tools and processes involved in B2B selling becoming increasingly complex, sales managers are often set up for failure from the start. The high turnover among sales representatives and the significant costs associated with hiring and training new talent only add to the burden, making the role of sales managers one of the most challenging in the business landscape today.

Revolutionizing Sales Management with AI

In today’s dynamic sales environment, AI and Machine Learning (ML) are essential tools that are reshaping the way sales management operates. By offering personalized training, automating administrative tasks, and providing data-driven insights, AI is setting a new standard for efficiency and growth in sales management.

Personalized Training and Coaching

Gone are the days of one-size-fits-all training programs. AI enables a more personalized approach to training, catering to the unique needs and learning styles of each sales representative. By analyzing sales interactions, AI identifies areas for improvement and tailors training content, ensuring that each member of the sales team receives the most relevant and effective coaching.

Administrative Automation: A Time Saver

AI shines in automating routine tasks that consume a significant portion of sales managers’ and representatives’ time. From generating personalized emails to logging customer interactions and scheduling meetings, AI tools streamline these processes, freeing up time for more strategic activities. This shift not only enhances productivity but also allows sales managers to focus on coaching and strategic planning.

Harnessing Data-Driven Insights

In the realm of sales management, data is king. However, the sheer volume of data can be overwhelming. AI algorithms excel in sifting through vast datasets, providing real-time performance metrics, identifying bottlenecks, and offering accurate forecasting. These insights empower sales managers to make informed decisions that drive better results for their teams and organizations.

AI is not just transforming sales management; it’s revolutionizing it. By providing personalized training, automating administrative tasks, and delivering data-driven insights, AI is enabling sales teams to achieve unprecedented levels of efficiency and growth. As we embrace these technologies, the future of sales management looks brighter than ever.

“In the fast-paced world of sales, managers are often overwhelmed by the sheer volume of data and tasks. AI offers a lifeline, helping them navigate the complexity with precision and efficiency, turning chaos into opportunity.”

Navigating the AI Implementation Journey in Sales Management

Integrating AI into sales operations isn’t just about deploying new technology; it’s about aligning it with your organizational culture, securing leadership buy-in, and ensuring your data is primed for action. Here’s how to make AI work for your sales team:

Organizational Culture: The Foundation of AI Adoption

Your company’s culture is the bedrock of successful AI integration. A culture that values innovation and is open to change will embrace AI’s potential to transform sales management. Conversely, a culture resistant to change may see AI as a threat rather than an opportunity. Cultivating an environment that encourages experimentation and learning is key to leveraging AI effectively.

Leadership Buy-In: Steering the Ship

Without the support of leadership, AI initiatives are likely to flounder. Leaders must not only endorse AI projects but also actively participate in their implementation. This involves allocating resources, setting clear objectives, and demonstrating a commitment to leveraging AI as a strategic tool for sales management success.

Data Readiness: The Fuel for AI

The adage “garbage in, garbage out” holds particularly true for AI in sales. The quality, completeness, and accessibility of your CRM data are critical. Before embarking on your AI journey, assess your data infrastructure to ensure it can support AI analysis. This step is crucial for avoiding pitfalls and setting the stage for meaningful AI-driven insights.

By focusing on these key areas, organizations can navigate the complexities of AI implementation in sales management, transforming challenges into opportunities for growth and efficiency. Remember, AI is not just a tool but a strategic asset that, when aligned with your organizational culture, leadership vision, and data capabilities, can significantly enhance sales management practices.

“Incorporating AI into sales operations requires more than just technological know-how; it demands a strategic approach that considers the unique dynamics of your organization. By addressing these foundational elements, companies can unlock the full potential of AI to empower their sales teams and drive unprecedented growth.”

Harnessing AI for Future Sales Success

The potential of AI in sales management cannot be overstated. As organizations look to navigate the complexities of modern sales environments, AI stands as a beacon of efficiency, growth, and strategic insight. By embracing AI, companies can unlock scalable success, empowering sales managers to lead with confidence and foresight. The path forward is clear: integrating AI into sales operations is not just an option; it’s a strategic imperative for sustainable growth and competitive advantage.

Learn what matters most to your customers with IDC’s AI Use Case Discovery Tool—find out more.

On June 10, 2024, Apple entered a new era of intelligence. At their annual Worldwide Developers Conference (#WWDC24), Apple unveiled how artificial intelligence will be embedded into their ecosystem and announced several enhanced features for iOS, iPadOS, and MacOS. These new smarter features will empower users through the use of AI.

This year’s WWDC marks a pivotal moment for Apple, being one of the most significant events in recent years. Since the introduction of the iPhone, the iPad, and the Apple watch, Apple has been the undisputable leader in terms of the user experience, and dominated sales of smartphones, tablets and smartwatches in value terms.

Over the last 17 years, Apple has not faced any other disruptive technology as potentially detrimental for its business and its future as AI, if not tackled in the right way. WWDC 2024 offered Apple and its CEO, Tim Cook, an opportunity to demonstrate how the company will lead in making AI a transformative, advanced, and intelligent experience for their users.

With smartphone, tablet and PC sales slowing down due to high adoption rates and offering just incremental improvements from the previous version of devices, Apple needs to reignite consumers excitement to encourage more frequent upgrades. We all remember the long queues outside Apple stores when a new iPhone was launched! The excitement generated by past product launches is critical to Apple’s business and brand.

AI Will Enable Apple To Offer Unique and Intelligent Features, Experiences and Services to Their Customers.

However, the key question remains: will these announcements be enough to secure Apple’s leading position? Many competitors (from phones to PCs vendors) have already revealed their AI strategies and devices. How can Apple stand out and how can a partnership with OpenAI help?

AI-Enabled Devices Will Be the Fastest Growing Segment in for Smartphones and PCs.

IDC forecasts that AI Smartphones to reach 170 million units in 2024, and AI PCs to account for nearly 60% of all PC shipments by 2027.

Historically, the App Store has been at the heart of the value proposition of Apple’s iPhone and the iPad. The slogan, “there’s an App for that” became iconic. However, AI is set to “kill” the apps and a new era is about to begin for Apple and the industry.

Previously, the more apps the smartphone (and the iPad) was able to run, and the more powerful the apps, the better the smartphone (or iPad). Today, the smartphone is not ‘smart’ anymore. With AI, the fewer apps needed and the more a phone can use data contextually to assist the user, the better the phone will be. This will revolutionize the user experience, requiring an operating system able to learn from all devices and services in Apple’s ecosystem. Apple’s full control of its ecosystem, hardware and software, and seamless integration gives it a significant advantage over competitors. This is particularly important when the experience will be defined by how well the phone “knows” the user, which can only be achieved by this seamless integration, while making sure the personal information and data remains private.

Although Apple is not the first to offer AI-enabled features, it is in its DNA to offer the perfect experience. AI will not just offer the best experience, but the most powerful, disruptive, personalized and private, and that’s exactly what Apple showed today with Apple Intelligence.

While AI-generated emojis will grab the headlines, Apple showcased how AI will empower users in several ways, particularly around productivity, education and entertainment. These are the areas where Apple already excels with its range of services and applications.

As User Interaction Shifts From Opening an App To Asking the Phone, Siri Will Be the Glue.

This killer feature will attract consumers to AI enabled devices. Siri will offer a unique way to interact with all Apple devices using our voice in a more personalized and conversational manner. It will become a true digital assistant, contextually understanding various aspects of users’ lives and providing human-like responses by accessing data across all devices to provide the right response to the users’ needs. This conversational digital assistant fully integrated with all devices will be a game changer, and I believe it will offer a compelling reason for many to upgrade their iPhones in the years to come.

Apple’s strength lies in the breath of its portfolio and its ecosystem. For consumers, it does not matter what an AI-enabled iPhone is, or how many TOPs it can run. What matters is how well a phone can assist users in managing their lives. By reducing the need to navigate multiple apps, Apple’s AI-enabled devices will offer a smoother, more intuitive and smarter experience. This marks the beginning of a new era for Apple and for their users.

For more insights and views, watch this conversation with Tom Mainelli at the Apple Park.

Learn what matters most to your customers with IDC’s AI Use Case Discovery Tool—find out more.

Carbon reporting has been much in the news over the past several years, with organizations under increasing pressure to track and disclose their carbon emissions.

IDC recently published a new document that offers a holistic assessment of the rapidly evolving landscape of carbon accounting and management platform vendors that are serving growing need for accurate, data driven emissions calculations and decarbonization strategy analysis.

As the global regulatory environment for climate risk and sustainability reporting continues to develop, organizations are under increasing pressure to report on their corporate emissions as well as their strategy for decarbonization. 

Organizations are also experiencing mounting pressure from customers and business partners for transparent carbon emissions data, indicating a business value impact in lost revenue opportunities associated with non-cooperation.  This is creating new demands on software platforms to support robust emissions calculations as well as provide analytical support to optimize decarbonization pathways. 

Key Trends Representative of Carbon Management Software Capabilities

The mounting organizational regulatory and business value impact of robust carbon accounting and management practices is leading more enterprises to depend on purpose specific applications to support these initiatives. Some important trends that are driving carbon accounting and management platform development include:

Data driven emissions calculations and reporting is elevating the importance of prebuilt connectors and APIs to source relevant data from billing systems, enterprise applications, third party sources, and IoT devices.  Centralized management of sourced data is vital to ensure consistency, accuracy, efficiency, transparency, regulatory compliance, scalability, improved decision-making and enhanced collaboration.
There is a wide breadth of organizational maturity that will dictate the scale of carbon accounting that an organization undertakes.  While many organizations continue to focus primarily on internal carbon emissions, regulation is beginning to mandate value chain emissions reporting which will significantly increase the complexity of emissions calculations.
Regulation is also mandating limited and eventually reasonable assurance of carbon emissions data requiring solutions that are highly auditable with transparent calculation methodologies and robust data verification capabilities.
As the complexity of carbon emissions reporting escalates, sustainability teams, often small in number, are becoming overburdened with routine tasks, which impinges on their availability for more strategic initiatives.  An important aspect of carbon management platforms will be workload offset enabled through automation and AI driven capabilities.
Regulatory and stakeholder requirements are extending expectations from reporting of historical emissions to forward looking decarbonization initiatives and goal management.  Supporting these requirements will necessitate advanced strategy, analytical and scenario planning features.
Sustainability is increasingly extending beyond an organization’s sustainability team as initiatives are incorporated into organization KPIs and values.  Carbon management platforms therefore should incorporate communication, collaboration and project management features that will foster cross team communication.
Expectations for corporate carbon emissions reporting and management are rapidly advancing.  Organizations are looking to software vendors to provide not only a robust platform but are also looking to these vendors for thought leadership, education resources and support.

In an era of escalating environmental scrutiny, mastering carbon accounting is not just compliance, but a strategic imperative for future-proofing businesses.

The 2024 IDC MarketScape for Worldwide Carbon Accounting and Management Applications evaluates 18 software vendors across 29 scoring criteria categories, including 18 capability categories and 11 strategy capabilities.

Software vendors included in the evaluation offer a carbon management software solution that is either a stand-alone product or a component of a broader platform. Vendors had to meet a minimum threshold of total employees as well as operate at a global scale (defined as having operations in at least two regions of the following regions: North America, South America, EU, APAC, Africa).

This research includes the analysis of eighteen sustainability software vendors including Acuity, Cority, EnergyCAP, FigBytes, GE Digital, Honeywell, IBM, Microsoft, Nasdaq, Normative, Persefoni, Plan A, SAP, Salesforce, Sphera, Sweep, UL Solutions and Watershed, who are positioned in the leaders and major players categories. The analysis identified that all 18 of the vendors have a strong carbon management solution, but some offer a more advanced solution set as well as a more innovative roadmap compared to others.

The carbon management software landscape has experienced explosive growth over the past five years which while providing better optionality, also presents organizations with increasingly complex choices in vendor selection.

This MarketScape is meant as a guide to help organizations evaluate software vendor platforms in order to identify the best platform for their organization for today as well as tomorrow’s requirements. It provides a comprehensive analysis of carbon management platforms, highlighting the increasing need for organizations to track, manage, and report carbon emissions amid evolving regulatory landscapes and stakeholder pressures. It evaluates vendors based on their capabilities and strategies to meet future customer needs, focusing on innovation, customer satisfaction, and the ability to support organizations in their decarbonization efforts.