By Darius Popa Microsoft priced its first Nvidia-powered Surface at $2,599.99 and claimed on stage that it doubles a MacBook Pro M5 on local AI prompts, without publishing how either figure was measured. The chip inside is built on Arm’s architecture, from the Cambridge company Nvidia failed to buy in 2022. Microsoft has priced its first Nvidia-powered laptop […] This story continues at The Next Web

Source:: The Next Web

By Alina Maria Stan HubSpot is eliminating about 660 roles, 7% of its workforce, in a restructuring its chief executive calls an AI strategy shift while insisting it is not driven by AI efficiencies. Its SEC filing concedes the timetable depends on local consultation law, which in Ireland means a statutory 30-day minimum and criminal penalties for ignoring it. […] This story continues at The Next Web

Source:: The Next Web

Cisco is adding AI agents to Webex group chats so colleagues can assign them work and share the results, part of a wider revamp of the Webex app.

Announced at the WebexOne conference Wednesday, users will soon be able to @mention agents in Webex “spaces” to help schedule meetings, take notes, and track tasks.

“You work with AI, but your teammates may never see that work — they can’t build on it, contribute to it, or reuse it,” said Amit Barave, Cisco vice president and general manager for Webex Suite and AI, in a blog post. “With Webex, agents become part of the team, participating where the work is happening.”

“This makes AI a shared capability for the team,” said Snorre Kjesbu, Cisco vice president and general manager for collaboration, in a separate blog post. “It can help people prepare together, carry decisions forward, and coordinate the next steps without losing the context of the conversation.”

As well as Webex spaces, the collaborative agents will be accessible during video and voice calls via the AI Assistant side panel, though these will only be visible to individual users, rather than teams, a Cisco spokesperson said.

Cisco’s announcement reflects the growing push from collaboration software vendors to bring AI agents directly into their applications, said Irwin Lazar, principal analyst at Metrigy. By positioning agents where employees are already collaborating, they are able to perform tasks such as managing meeting agendas, facilitating, and providing contextual information into meetings.

“We’ve seen similar efforts by Slack, with Claude Tag, and with Zoom via ZoomMate,” said Lazar. “Like the others, the strength of the agent is dependent on its access to information, so the key is enabling connectivity to external data sources such as CRM, ERP, project management, etc.”

The changes are part of a wider Webex app refresh app that includes a new personalized landing page to highlight work priorities and upcoming meetings, as well as suggest follow-up actions, such as responding to messages or reviewing meeting recaps.

“The new assistant literally knows what you are doing and your upcoming schedule and knows more than other major providers,” said Jim Lundy, CEO of Aragon Research. “In fact, I’d say that their assistant could be sold unbundled.”

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Cisco

In addition, Cisco is extending the range of third-party agents accessible from Webex, too. Anthropic’s Claude Managed Agents — cloud-hosted agents that process multi-step tasks in the background — can be added to group conversations as a team member to complete tasks, as well as OpenAI’s recently announced “dot” agents.

Cisco also unveiled more of its own native Webex agents. Personal Agents for Webex Calling can screen calls to help users avoid missing an important call when they’re unavailable to speak. The agents can “converse with callers to understand their needs and determine urgency, prioritize what matters most, and take action on your behalf,” Barava said. Personal Agents for Webex Calling will be available in the first quarter of 2027, alongside the new Webex app, collaborative agents, third-party agents.

A previously announced Translator agent is now in “controlled availability” ahead of a general release in November. This provides real-time translation in the Webex app, as well as Cisco 9800 Series Desk Phones, with support for ten languages: English, French, German, Hindi, Italian, Japanese, Korean, Mandarin, Portuguese, and Spanish.

An AI Coach agent for Vidcast — Cisco’s tool for short form, asynchronous video messaging in Webex — is aimed at helping users improve communication performance. “The AI Coach watches and listens while a presenter delivers, reacts to pacing, tone, and word choice as they happen, and asks the questions a live audience would,” said Barave. The AI Coach agent is available now.

Metrigy’s Lazar said he has witnessed an uptick in business demand for agentic tools in collaboration applications generally. “They offer the potential to bring context into meetings, saving time and increasing focus. Cisco’s aim is to ensure that the Webex App can remain the place where people work, rather than other apps or AI interfaces like Claude Cowork,” he said. “I would say the only weakness in the Cisco portfolio now is ability to capture data from non-Webex meetings. They lack the capability that Zoom now has to capture audio from third-party or external meetings.”

A Cisco spokesperson said that some Webex AI capabilities are available at no extra cost in Webex Suite, which costs $25 per user each month, and Enterprise tiers. More advanced features — such as Polling and Translator agents, the Personal Agents for Calling, and collaborative agent functionality — will require a new “Enhanced AI Offer for AI” add-on. This will be available in the coming weeks, Cisco said, though pricing for the add-on was not provided.

Cisco didn’t specify if any of the AI features will require any additional, usage-based costs on top of fixed subscription fees. The company recently stated that the Translator agent provides 50 minutes of translation per user each month, with additional usage requiring an “add-on.”

Source:: Computer World

The lack of artificial intelligence features in LibreOffice should be considered a feature in and of itself, according to the free office suite’s creators. The Document Foundation, the organization behind the free office suite. The Document Foundation, the organization behind the free office suite project, writes in a blog post that, for the time being, the software will not include any AI in the standard installation.

The decision is not motivated by any principled opposition to AI, the post states, but rather by the fact that the technology doesn’t currently meet the project’s requirements for privacy, user control, and open standards.

For example, users must be able to decide for themselves where the AI model runs. The Document Foundation also requires that any future AI solution not collect telemetry or lock users into a single vendor. AI-generated content must also use the open document format ODF, and AI features must be entirely optional.

However, if an AI solution emerges in the future that can meet all these requirements, The Document Foundation will consider it.

This article originally appeared on Computer Sweden.

More on LibreOffice:

Austrian Armed Forces switch from Microsoft Office to LibreOffice

LibreOffice downloads on the rise as users look to avoid subscription costs

Source:: Computer World

By Hisan Kidwai The festive season is finally here, and so are Flipkart’s Big Billion Day and Amazon’s Great…
The post These ASUS Laptops Are Seeing Huge Price Cuts During the Festive Sales appeared first on Fossbytes.

Source:: Fossbytes

By Hisan Kidwai Something strange is coming to Erangel in BGMI. Starting October 8, players can take on Kiaraa,…
The post BGMI Kiaraa Event Arrives October 8 With a New World Boss in Erangel appeared first on Fossbytes.

Source:: Fossbytes

By Cristian Dina Sierra and Meta are developing Personal Agent Protocol, an open standard defining how personal AI agents authenticate with businesses and what those businesses let them do, with Genesys, Instinct, Rocket, Shopify, Stripe and Walmart. A v0.1 specification is due this month, and payments are listed as a future extension rather than part of it. Meta […] This story continues at The Next Web

Source:: The Next Web

By Ana Maria Constantin Google has released EmbeddingGemma 2, an open 740-million-parameter model that maps text, code, images, audio and video into a single space and runs entirely on a phone or a small board. It is licensed under Apache 2.0, has had no safety tuning, and Google says performance is not equal across the 100 languages it supports. […] This story continues at The Next Web

Source:: The Next Web

A number of studies reported a decline in tech jobs in September as the US continues to get squeezed by geopolitical and economic instability.

Tech consortium CompTIA said 10,350 positions in the technology sector were lost in September, lower than the 14,700 positions cut in August.

But economy-wide, tech jobs — which include IT roles not associated with tech sector — took a bigger hit. Tech jobs across all industries fell by about 6,000, a sharp reversal from the 86,000 added in August.

CompTIA’s report is based on an analysis of the US Bureau of Labor Statistics’ September jobs report, which found that only 29,000 nonfarm jobs were added in the US in September, lower than expectations. The US added 133,000 jobs in August.

Tech worker unemployment ticked up to 3.3%, but that was below the 4.2% national rate, according to CompTIA. The strong August numbers raised hopes that tech jobs were stabilizing, but September’s numbers dashed that hope.

Separately, tech companies announced 10,799 job cuts in September, a 77% rise from the 6,103 announced in August, according to numbers from Challenger, Gray & Christmas.

The tech sector has cut 165,925 jobs this year, up 54% compared to the same period in 2025. US employers cut 43,281 jobs across all sectors in September, compared to 52,881 in August.

Employers are taking a wait-and-see approach in hiring due to rising costs and political uncertainty, despite fewer jobs getting cut compared to August, said Andy Challenger, chief revenue officer at Challenger, Gray & Christmas.

“Employers are facing high energy costs, an uncertain war in Iran, a rate hike that could make hiring more expensive, plus the likelihood of surging healthcare costs,” Challenger said.

Amid the uncertain environment, employers are hiring cautiously, as jobs are tied directly to strategic business priorities, said Ger Doyle, ManpowerGroup’s regional president in North America.

“The market is no longer defined simply by how many people employers hire, but by how precisely they hire,” Doyle said.

Earlier this year, AI was often cited as a main reason for job losses. But that wasn’t the case in September. AI was cited for only 3,961 of the 43,281 job cuts, or about 9% of the month’s total, Challenger, Gray & Christmas said.

Overall, AI was cited for 120,136 job cuts so far in 2026, which is 21% of all cuts.

Even as tech jobs decreased overall, CompTIA noted, Lightcast job posting data showed that US employers posted 272,040 new IT job openings in September, an increase of 16% from September 2025. That mismatch indicates a search for specific skills.

ManpowerGroup said AI skills are the most in demand. “The roles that matter most also take the longest to fill,” Doyle said.

Job postings typically stay open for 61 days, while filling engineer roles typically takes 77 days, Doyle said.

Active job postings requiring AI-related skills totaled 349,821 in September, an increase of 32,327 postings from August, CompTIA said.

Source:: Computer World

When it comes to consumer protections, Europe is following its own path. That may be visible in its quixotic-seeming decisions that allegedly prevent Apple from introducing Siri AI in the European Union. It’s time to begin to grapple with what those decisions mean.

I think the EU has got it wrong in how it has chosen to enforce its Digital Markets Act against Apple. The refusal to figure out a mutually satisfactory way to apply the intent of the DMA on Apple’s business practices while protecting its stated values around privacy is a failure of imagination and diplomacy. Apple and Japan previously reached an agreement that achieved positive impacts for third-party developers while protecting the product design integrity and customer privacy the company and its customers care about.

Prevention is not cure

That lack of deal-finding in the EU is preventing the introduction of Apple Intelligence and Siri AI to customers in the trading bloc. 

When it announced these AI features, Apple told us it had proposed some kind of technological fix that would provide third-party product makers, including AI product makers, with user information to drive their products while also protecting user privacy. Europe declined to work with Apple on those terms, which is why the company has not introduced Siri AI there. 

European regulators would, of course, disagree with that account, but this is what has been suggested.

What Apple’s privacy fix could look like

More recently we got the chance to see what that kind of AI-enabling tech privacy protection might look like when Apple introduced Audio Intelligence, particularly Siri Recap. This relies on a semi-magical selection of complementary technologies that enable the feature while protecting personal privacy.

It does this by analyzing audio in real time, summarizing it, removing personally identifiable data from it, and sending a vastly reduced and anonymized data set to the cloud for final processing. The idea here is that your data for the most part is only ever handled by your device, is not saved, and only just enough information is passed down the line. 

I believe this hints at the technical approach Apple had hoped to build to protect Siri AI in the EU. Distilling and anonymizing personal data while still making it possible to run effective AI tools is the name of that game. Extending that approach to third parties and other domains — including video — will take time, which is what Apple asked Europe to provide.

The EU, we’re told, didn’t budge. That’s a shame, in part because European customers won’t get to use Apple’s more private take on AI, but also because they will continue to find their data exposed to AI firms that are not focusing on privacy. 

Europe wants its own AI

I suspect Europe doesn’t mind that too much, because it is hoping to foster the evolution of its own AI solutions, rather than becoming even more reliant on US technology firms. 

The EU is already investing heavily in tech sovereignty. Its TESTA-EIRIS system, for example, may have a silly name but is an attempt to build a regional, localized, sovereign communications infrastructure for European governments and institutions. This infrastructure will no doubt be used within the implementation of localized AI systems and services. 

You cannot underestimate the drive to sovereign tech solutions; it’s an international movement and all about building national resilience and crisis independence. A 2025 McKinsey report showed that 71% of executives, investors, and government officials worldwide now see sovereign AI as an existential concern. That means many nations will be looking to deploy their own region-specific solutions. It also means Big Tech firms like Apple — or US frontier AI firms, given their market share — must identify new business practices that respect international differences.

Surely there’s a middle ground?

This inward-focused drive toward sovereign tech reflects a wider malaise in international relations. Ironically, it is one that might benefit from the kind of “private by design” approach Apple is pioneering with Audio Intelligence. 

Will it be possible for Apple’s systems to use a tech like this to empower third-party systems while protecting personal privacy? If Apple achieves this, it should help sovereign tech deployment, as it builds in privacy at the end-user layer, which can then be picked up by whatever national AI solutions eventually emerge. 

It probably isn’t enough for the EU sovereign vision, of course, but could be a positive compromise pending the creation of a viable European hardware solutions manufacturer, which seems a very, very, very long way away. But positive compromise doesn’t appear to have been the hallmark of Europe’s DMA dealings with Apple so far, which may well be why the latest word from Mark Gurman is that Europeans must expect to wait at least five more months, and potentially much longer, before they even hear a hint that the two sides have reached a rapprochement. 

In the meantime, European users on mobile devices remain more likely to use Claude or ChatGPT than less popular EU-made AI services, such as Mistral. All without the kind of privacy protections in place Apple aspires to deliver. 

Surely there’s a middle ground? 

Surely Apple’s promised technology to enable AI while protecting privacy is something the EU would benefit from? Maybe the two sides should try to figure something out. 

Now please subscribe to my daily, human-curated Apple-related news headline feed at The Core, or follow me on BlueSky, LinkedIn, or Mastodon.

Source:: Computer World

The average enterprise pays for over 100 software applications, yet employees actively use only a fraction. This digital bloat drains your budget and productivity. When systems do not connect, teams face disconnected data, inconsistent reports, and endless manual workarounds.

Building a Modern MarTech Stack is not about adding more tools to your arsenal. It means creating a connected system that drives real business results. To succeed, move beyond simple purchasing and use a strict, finance-led evaluation process.

This guide offers a practical framework for auditing your current environment and consolidating overlapping capabilities. We will show you how to test new alternatives and apply strict governance.

By focusing on data readiness and workflow fit, you can turn a fragmented setup into a streamlined growth engine. Stop paying for complexity and start investing in efficiency.

What the Case Study Reveals About MarTech Stack Fragmentation

When a marketing team grows faster than its processes, technical debt can overwhelm even talented professionals. Many organizations buy software for urgent problems without considering its long-term effect on their technology ecosystem.

Meet the Marketing Team Behind the Stack Audit

A mid-sized software firm scaled its operations quickly over three years. Its marketing team grew from five people to thirty, and each hire preferred different software platforms. Without a central governance strategy, the team soon built a bloated set of disconnected applications.

Leaders eventually saw that rapid expansion had created a fragmented environment. They paid for several subscriptions with nearly identical functions but could not create one accurate customer acquisition cost report.

How Duplicate Tools Created Cost, Data, and Workflow Problems

The audit found a chaotic mix of overlapping subscriptions. The team used three email marketing platforms, two separate CRM instances, and four analytics tools. This redundancy caused inflated operational costs and major data silos.

Because the systems did not communicate, the team could not track a lead from the first click through the final sale. Staff spent hours moving CSV files between systems to match basic performance metrics. This work reduced productivity and caused frequent reporting errors.

Why More Modern Marketing Technology Did Not Automatically Improve Results

The firm first believed that modern marketing technology would fix its efficiency problems. Instead, new tools exposed and worsened its process gaps. Advanced software without an integration plan created more places for data to disappear.

Better results require more than the latest features. The team must judge each piece of modern marketing technology by its role, integration abilities, and measurable value. Without accountability and clean data flows, costly platforms will not provide the expected return on investment.

Building a Modern MarTech Stack Around Business Outcomes

Your technology stack should link your company’s financial goals with daily marketing work. A strong martech strategy starts with clear business results, not software features or vendor promises. These results might include higher customer lifetime value or a shorter sales cycle.

Translate Revenue Goals Into Marketing Technology Requirements

To build a strong stack, translate revenue goals into clear technical needs. If you want better pipeline quality, your martech strategy must prioritize lead scoring and data enrichment tools. Each software choice should support your quarterly targets.

Do not buy tools based on polished sales demonstrations. Clean metric definitions and usable source data matter more than a long list of bells and whistles. Each tool must fix a specific bottleneck blocking your team from reaching revenue milestones.

Connect Customer Journeys to the Marketing Technology Stack

Modern marketing requires a clear view of customer interactions across many channels. Your technology should move data smoothly from the first touchpoint to the final conversion. When systems are disconnected, you cannot provide a personalized experience.

Map each customer lifecycle stage to find where your tools succeed or fail. If a customer moves from an email campaign to your website, the transition should feel invisible and preserve useful data. Integration is the backbone of a successful customer journey, giving your team one view of every prospect.

Set Success Measures for Efficiency, Data Quality, and Campaign Performance

Clear success measures help maintain a healthy stack over time. Set benchmarks for efficiency, data completeness, and campaign performance early in planning. These metrics show whether your martech strategy delivers the expected return on investment.

Focus on attribution confidence and reliable reporting. If data is fragmented or inconsistent, your team cannot make informed decisions. Strict data quality standards keep your technology useful instead of creating operational friction.

How to Inventory Every Tool, Integration, and Owner

You cannot manage what you cannot see, so a thorough inventory supports success for your marketing technology stack. Many organizations face hidden costs and security risks because they lack a clear view of their software ecosystem. Documenting every asset helps you make informed decisions about your digital infrastructure.

Capture Core Platforms, Point Solutions, and Shadow IT

A complete inventory must cover more than the enterprise systems managed by your IT department. You also need to uncover shadow IT, including unauthorized extensions, spreadsheets, and niche tools bought with company cards. These hidden solutions often duplicate functions and create major data silos.

Start by surveying team leads to identify every application used in daily workflows. Capture sanctioned platforms and the smaller point solutions teams depend on. This comprehensive approach ensures that no tool stays hidden during your audit.

Document Each Tool’s Users, Purpose, Cost, and Contract Terms

After listing the tools, record the details that define each tool’s value. For every entry, document its main business purpose, active users, and contract terms. Also track renewal dates and total subscription costs to avoid unexpected budget spikes.

Assign an accountable owner to every tool in your marketing technology stack. This person manages access, monitors usage, and keeps the tool aligned with business goals. Clear ownership prevents the “orphan software” problem, which can drain budgets after its original purpose ends.

Map Data Flows Between Salesforce, HubSpot, Google Analytics 4, and Other Systems

The final step is visualizing how your systems communicate. Map data flows between core platforms such as Salesforce, HubSpot, and Google Analytics 4. Understanding these movements is essential for maintaining data integrity and security.

Use data lineage and role-based access controls to check that your integrations work reliably. Documenting these connections helps you find where data may become stuck or corrupted. A well-mapped marketing technology stack helps your team trust insights from reporting tools.

How to Audit Adoption, Redundancy, and Technical Fit

Unused features and duplicate platform abilities often hide costs. By optimizing martech tools, organizations can recover budget and simplify daily work. A thorough audit examines how your team uses each tool in its current stack.

Measure Whether Teams Use the Features They Pay For

Review login frequency and feature reports first. Many platforms show which modules staff never use. If your team pays for advanced automation but schedules basic emails, you may overspend on unnecessary complexity.

Compare assigned licenses with active user lists. This check prevents payments for departed employees or inactive accounts. Optimizing martech tools means matching subscription tiers to your marketing department’s needs.

When usage is low, consider downgrading or combining service plans.

Find Overlapping Capabilities Across Email, CRM, Analytics, and Automation Tools

Redundancy often enters a stack when departments buy separate solutions. Your CRM may include email features that duplicate a standalone email service provider. This overlap fragments data and makes teams manage several logins for one task.

Review workflow records for manual data transfers between overlapping systems. Optimizing martech tools means finding these bottlenecks and selecting one source of truth for customer data. Fewer platforms can improve team efficiency and data consistency.

Separate Genuine Platform Gaps From Training and Process Gaps

Not every performance problem comes from a faulty tool. Sometimes, teams lack training and cannot use a platform well. Before replacing a system, interview power users about their daily frustrations.

If software has the needed capability, focus on better documentation and hands-on workshops. If it lacks essential integrations or cannot scale, you have found a genuine technical gap. Separating these cases is vital for optimizing martech tools and supporting long-term growth.

Evaluating Data Quality and Integration Readiness

Before adopting new platforms, verify that data moves smoothly across your entire ecosystem. A truly integrated marketing technology stack needs more than software; it needs clean, reliable data flow. Without it, your team risks operational failure and fragmented customer insights.

Test Identity Resolution, Consent, and Field Consistency

Successful data management starts with accurate identity resolution. Ensure one customer profile stays consistent across your CRM, email platform, and analytics tools. Standardizing field naming conventions prevents duplicate records and synchronization errors.

Also, verify that consent status travels with each user record. If a customer opts out in one system, that preference must spread instantly. This consistency defines high-performing integrated marketing technology.

Trace Lead, Account, and Customer Data Across the Stack

To validate your architecture, trace records from capture through the full customer lifecycle. Follow a lead from a landing page into your CRM and then into your reporting dashboard. This process reveals hidden gaps in account hierarchies and data mapping.

Testing these paths shows where data may be lost or corrupted. Reliable data tracking ensures accurate, actionable marketing attribution. It also confirms that your sales team receives the right context for every account.

Assess Integration Reliability, Latency, and Error Handling

Even the best tools fail when their connections are unstable. Measure latency between systems to ensure your automation triggers fire in real-time. High latency often causes missed opportunities and poor customer experiences.

Also, evaluate how systems respond when an integration breaks. A robust integrated marketing technology setup includes automated alerts and recovery protocols. These features protect workflows from unexpected downtime and data loss.

Protect Governance, Privacy, and Regulatory Requirements

Treat data security and compliance as design requirements, not afterthoughts. Ensure your stack follows regional privacy laws and internal data residency policies. Auditability is critical for maintaining trust with customers and stakeholders.

Use strict permissions to control who can access or change sensitive customer information. By prioritizing governance, you build a secure environment that supports long-term growth. This proactive approach reduces risk while maximizing the value of your technology investments.

Creating a Consolidation Business Case

Many organizations struggle to identify the best martech solutions because they favor popular vendors over operational needs. A sustainable stack requires tools that fit your business model, not just attractive features. A strong business case gives stakeholders and leaders evidence for needed changes.

Rank Tools by Strategic Value, Business Risk, and Switching Difficulty

Start by scoring your current inventory on three critical dimensions. Strategic value measures how directly a tool supports revenue growth and customer retention. Assess business risk, including data security vulnerabilities, compliance gaps, and vendor stability.

Finally, assess the switching difficulty of each platform. Estimate the time, technical effort, and possible downtime needed to move data or retrain staff. Tools deeply embedded in workflows but offering low strategic value are prime consolidation candidates.

Calculate Total Cost Beyond Subscription Pricing

The true price of a tool often hides beyond the monthly invoice. When seeking the best martech solutions, calculate the Total Cost of Ownership (TCO). This includes hidden costs such as implementation fees, ongoing integration maintenance, and specialized training.

Include administrative overhead and security monitoring costs. A tool needing extensive manual data cleaning or custom coding costs far more than its sticker price. These factors keep financial projections accurate and defensible.

Choose What to Retain, Replace, Merge, or Retire

After gathering your data, categorize every tool: Retain platforms that offer high value and low risk. replace platforms that no longer meet your technical requirements. You may merge overlapping functions into one, more powerful system.

If a tool offers little utility or adds needless complexity, it is time to retire it. This framework helps you present a logical, evidence-based strategy to your team. These categories keep your stack lean, efficient, and aligned with long-term goals.

Using a MarTech Strategy Scorecard to Compare Platforms

A formal scorecard turns subjective opinions into objective data, supporting better decisions. By avoiding gut feelings, teams keep their mar tech platform selection aligned with long-term business goals. This process helps stakeholders see trade-offs and explain investments to leaders.

Define Weighted Criteria for Mar Tech Platform Selection

Begin by weighting categories according to their impact on your organization. Prioritize factors like integration capabilities, data governance, and security over secondary features. Scoring each vendor against these criteria creates a clear needs hierarchy for the final decision.

For example, security and compliance deserve the highest weight in a highly regulated industry. This choice helps each tool meet your internal control environment requirements. Prioritizing these technical requirements early prevents choosing a platform that looks great but cannot integrate with existing infrastructure.

Compare Total Value Rather Than Feature Counts

Many teams choose software because it offers the most advertised features. Yet dozens of unused functions can create needless complexity and bloat. Focus instead on the actual workflow fit and the platform’s ability to solve specific business problems.

Assess total value by considering ease of use and implementation speed. An intuitive platform can increase adoption, which helps deliver a positive return on investment. True value lies in efficiency, not in the number of dashboard buttons or menus.

Involve Marketing, Sales, IT, Finance, and Legal in the Decision

A strong mar tech platform selection needs input from several departments to avoid blind spots. Marketing and Sales must confirm customer-journey support, while IT reviews the technical architecture. Finance and Procurement check contract terms against budget cycles, while Legal handles privacy and risk assessments.

Early stakeholder involvement builds support and reveals roadblocks before they become costly issues. This collaboration makes the final choice more than a marketing tool: it becomes a secure and scalable asset for everyone.

Testing the Best MarTech Solutions Before Making a Commitment

Buying new software takes more than a polished sales pitch. It requires careful testing through a structured pilot program. Testing beyond vendor demos shows whether the best martech solutions work in your business environment.

Build a Proof of Concept Around a Real Customer Journey

To judge a platform, map it to a real customer journey. Use a lead from your actual sales funnel instead of generic test data. This test shows how the software handles your business logic and complex data requirements.

Test Lead Capture, Segmentation, Automation, Reporting, and Handoffs

Your pilot should follow a lead from capture to the final sales handoff. Check that consent management stays intact at every stage. Test Automation triggers for speed and accuracy, and audit reporting dashboards for actionable insights, not just vanity metrics.

Evaluate Vendor Support, Documentation, and Implementation Partners

Technical capability is only one part of choosing the best martech solutions. Assess the vendor’s support response and the clarity of its technical documents. If you use third-party implementation partners, check whether they can connect the tool to your current infrastructure without unnecessary downtime.

Set Clear Pass-Fail Criteria for the Pilot

Before the pilot starts, define clear success measures that all stakeholders approve. If the platform misses these benchmarks, reject it or require fixes before making a long-term commitment. These strict pass-fail criteria reduce the risks of poor adoption and wasted budget.

Planning Mar Tech Implementation Without Disrupting Campaigns

A successful mar tech implementation adds new systems without stopping active marketing campaigns. It modernizes your infrastructure while keeping leads and customer engagement moving. This steady flow supports business growth.

Sequence Migration by Data Dependencies and Business Risk

Do not replace every tool in your stack at once. Prioritize migration by system data links and the revenue risk of failure.

Map dependencies among your CRM, marketing automation, and analytics platforms. By sequencing your rollout, you reduce the risk of breaking data pipelines that support your sales team.

Protect Active Campaigns, Reporting Continuity, and Historical Records

Data integrity is essential during a transition. Keep historical records accessible, and keep reporting dashboards accurate throughout the mar tech implementation process.

Avoid starting over if it would erase valuable performance data. Instead, connect legacy systems with new platforms for a seamless transition during ongoing marketing efforts.

Assign Ownership for Configuration, Migration, Testing, and Approval

Clear accountability helps prevent mistakes that cause project delays. Assign an owner to each migration phase, including configuration and final system validation.

Set formal approval checkpoints for marketing, IT, and sales stakeholders. They must approve the new setup. This structured approach meets each department’s needs.

Train Teams Before the New Workflow Becomes Mandatory

Technology works only when people can use it well. Prioritize training that shows how new tools improve daily tasks, not only technical features.

Introduce the workflows before they become mandatory. This gives your team time to share feedback and adjust to the new environment. This proactive mar tech implementation strategy reduces resistance and helps your team hit the ground running on day one.

Measuring the Results of the Consolidated Stack

A clear measurement plan helps prove the value of a streamlined stack. By tracking key KPIs, you can show how your martech stack consolidation improves business results. This data tells a clear story about efficiency and growth.

Compare Pre- and Post-Consolidation Operating Costs

The clearest success signal is a lower total cost of ownership. Compare old software subscription fees with the new, leaner budget. Do not forget hidden costs, such as implementation overhead and maintenance hours.

Eliminating duplicate licenses and similar features can create Significant savings. Track these savings to show stakeholders a clear return on investment. They also create a baseline for future budget planning.

Track Campaign Speed, Data Completeness, and Workflow Reliability

Better marketing technology stack performance shows through greater efficiency. Measure the time needed to launch a campaign, from ideas to execution. Many teams cut launch times by 50% or more after consolidation removes manual data entry.

Check data completeness and synchronization error rates across your core platforms. A reliable stack should reduce broken integrations and data silos. Workflow reliability gives your team more time for creative strategy and less time troubleshooting.

Measure Improvements in Lead Management and Customer Experience

Your stack should serve customers, so track lead velocity and journey mapping. For example, cutting a three-week lead close time to under one week shows strong progress. Consistent data flow supports more personal interactions at every touchpoint.

Study how your consolidated tools affect the customer experience. When systems connect well, you can deliver useful content at the right time. Better lead management is directly linked to higher conversion rates and stronger revenue outcomes.

Use Quarterly Reviews to Prevent New Tool Sprawl

Even a well-optimized stack can develop “feature creep” without regular checks. Hold quarterly reviews to decide whether new tools are needed or existing platforms can meet the need. This approach prevents fragmented systems from returning.

Use these reviews to check user adoption and find features that teams underuse. Governance is a continuous process requiring attention from marketing and IT leaders. Close monitoring keeps your technology a strategic asset, not a growing liability.

Lessons From the Case Study for Long-Term Stack Governance

Establishing robust martech governance stops redundant tools and fragmented data from growing over time. After you consolidate the stack, disciplined oversight protects those gains. This keeps your organization from returning to uncontrolled tool growth and data chaos.

Make Tool Requests Follow a Consistent Evaluation Process

Every new software request must pass through a standard review process. The process should assess the business need, data access, and integration effects. A formal review of costs, security, and legal compliance gives each addition a clear strategic purpose.

Assign ownership before signing any contract. This limits shadow IT and keeps someone accountable for the tool’s performance and eventual retirement.

Maintain a Living Architecture Map and Data Dictionary

A static document cannot keep pace with modern marketing needs. Maintain a living architecture map to show how systems connect and share information. The map gives your entire team one trusted source of truth.

Pair it with a comprehensive data dictionary, so everyone defines metrics like “lead” or “customer” the same way. This shared meaning protects data integrity as customer journeys change.

Balance Flexibility With Standards for Integrated Marketing Technology

Effective marketing technology governance does not block innovation. It lets teams test ideas safely within clear guardrails. You should encourage approved platforms while limiting unvetted point solutions.

Clear standards for integration and data security support agility without weakening system stability. This balance helps maintain a high-performing, integrated ecosystem.

Define When the Stack Should Expand, Consolidate, or Be Rebuilt

Your stack is a changing asset that needs active lifecycle management. Define triggers for when to expand, consolidate, or rebuild your setup. Triggers may include a specific revenue milestone, a business strategy shift, or lower system performance.

Review these triggers often to prevent technical debt from building. Treating your stack as a living entity keeps technology a competitive advantage, not a burden.

Conclusion

Success in the digital landscape takes more than buying the latest software. Building a Modern MarTech Stack depends on matching your tools with clear business outcomes, not chasing feature lists.

Prioritize disciplined audits and reliable data so your systems work together. Adding more platforms rarely improves results when internal governance and team adoption remain weak.

Test real customer journeys to confirm that your setup works. Compare your investments’ total value with your campaigns’ actual performance. Protect data quality and maintain operational control to keep your infrastructure agile.

Building a Modern MarTech Stack requires an ongoing commitment to efficiency and clarity. Keep your architecture flexible for growth while maintaining structure for accountability. Review integrated systems regularly to prevent tool sprawl and keep marketing operations running at peak performance.

By Cristian Dina Nokia’s chief executive Justin Hotard says the industry would build data centres twice as fast if memory and energy supply allowed, and that demand would hold even without a new frontier model for three years. Bain and a paper presented at the Brookings Papers on Economic Activity both question whether the revenue exists to pay […] This story continues at The Next Web

Source:: The Next Web

By Alina Maria Stan Republican senator Bernie Moreno has accused Anthropic chief executive Dario Amodei of taking an “alarmist approach” to AI. He did so in a letter sent on Monday, ahead of Anthropic’s expected stock market listing. Axios first reported the letter. “I do not understand how you can ask them to invest their hard-earned savings in Anthropic’s […] This story continues at The Next Web

Source:: The Next Web

By Deepti Pathak After introducing the S2 a couple of months back, vivo is introducing the new S2 FE…
The post Vivo S2 FE India Price and Specifications Tipped Before Launch appeared first on Fossbytes.

Source:: Fossbytes

By Deepti Pathak Primebook has officially launched the Primebook 3 Max, its first laptop under the third-generation lineup. The…
The post Primebook 3 Max Debuts with MediaTek Genio 720 and Expanded PrimeOS appeared first on Fossbytes.

Source:: Fossbytes

Most organizations have been largely unable to measure financial returns from AI, but analysts say new ways to calculate return on investment are emerging.

“There’s a delay between the development of technology, even the investment in the technology, and the value that an organization can capture from it,” said Michael Chui, a senior fellow at McKinsey.

But more executives are asking questions. “The CFOs are asking CIOs, investors are asking CEOs: ‘Where’s the ROI from this stuff, already?’” he said.

In McKinsey’s “State of AI” survey released in August, about 80% of respondents said AI improved their productivity. But only 37% said AI’s impact showed up in profits, about the same as last year. An even smaller number — only 6% — said AI delivered significant value and accounted for at least 5% of their operating profit.

In other words, there’s a drop-off between the value that individual workers are getting from AI and the value that organizations are getting from AI, Chui said.

The biggest gains will come from redesigning workflows and processes in which humans and AI agents work together, according to McKinsey’s Technology Trends Outlook. Layering agents onto existing processes isn’t enough.

“Usually an end-to-end workflow involves multiple individuals, and completely redesigning that with the use of AI… is characteristic of high-performing companies,” Chui said.

Controlling costs

Managing token costs and applying the right model for a task is part of realizing better returns, Chui said. “In many cases, there just isn’t transparency… Which workloads are actually driving your costs?” he said.

Three out of five IT leaders are worried about AI agents running up unexpected costs, and this is already happening, said Gareth Herschel, a vice president analyst at Gartner, during a keynote at Gartner’s Data & Analytics Summit in Mumbai.

“Some organizations have already discovered that the cost of tokens for coding assistance is much higher than the cost of human software developers,” Herschel said.

As more agents work together, “your financial risk only grows. It’s like giving your teenager your credit card… I’m sure you will learn a lot, but mostly from the bill,” said Robert Thanaraj, a senior director analyst at Gartner and a co-speaker at the Mumbai keynote.

Companies should track costs in prototyping, such as finding the cost of an individual agent per completed task, Thanaraj said. “It’ll help you to evaluate different large language models or help you to go with a more affordable option, such as smaller language models or open weights model.”

A wider lens for ROI

Analysts highlight numerous challenges in calculating AI ROI, such as unexpected costs, poor data quality, failure to scale, and slow adoption among users.

But executives are skilling up in tracking what they spend on AI and the returns, said McKinsey’s Chui. “Between the CFO and the CIO, we’re starting to see these disciplines emerge.”

In 2025, the odds of an AI initiative achieving ROI were one in five, the Gartner analysts said in their keynote.

“ROI matters, but to achieve it, we must think of it not just as a financial metric, because value isn’t always just about money,” Thanaraj said.

Companies should tie AI projects to both financial and non-financial outcomes, part of what Gartner calls a “return on intelligence.”

“We need to shift the emphasis from cost to value,” Herschel said. “The outcomes can be financial, such as revenue, but they can also be non-financial, such as citizen experience.”

The right foundation: context, infrastructure, governance

The Gartner analysts said achieving ROI on AI requires a strong technical and contextual foundation.

“Governance adds trust. Context adds meaning. Without strong foundations, AI may well stand for amplified ignorance,” Thanaraj said.

For example, data quality can be a roadblock. “Without clear context, LLMs are just guessing,” Thanaraj said, and that amplifies misunderstanding. Poor data and poor AI design mean more hallucinations and bad output.

“You can’t buy this context layer off the shelf. It has to be built to fit your needs,” Herschel said.

A strong technical foundation, such as a robust networking backbone for data movement, is critical, said Jack Gold, principal analyst at J. Gold Associates.

“Agent-to-agent interactions will become commonplace and mission-critical, even as the number and distribution of agents expands dramatically to include interactions across remote agent locations and devices,” Gold wrote in a research note.

A majority of organizations are establishing harnesses — the software layer that controls and coordinates models, tools, and workflows — to govern AI use in business. According to a global KPMG survey released last month, 55% of organizations have a formal AI harness layer. That rises to 86% among organizations reporting established ROI.

Organizations that “combine clear accountability, coordinated governance, resilience, and reliable value measurement will likely be best placed to turn broad adoption into sustained performance,” KPMG said.

Source:: Computer World

Apple has been forced to make macOS even more locked down, to the dismay of some developers. It has announced plans to introduce more user-facing control over the process of giving apps Full Disk Access.

Some developers are upset, believing this will put more barriers in place to those creating apps outside the App Store. Endpoint security vendors voiced some concern but understand the cause: “poorly written/insecure/greedy AI agents/assistants insisting on Full Disk Access, and then once granted/obtained, abusing that, to access ,” as Objective-See co-founder Patrick Wardle wrote on X.

Explaining its plans, Apple says it will still make it possible for customers to choose to enable Full Disk Access; it’s just going to make the decision much more intentional, with additional steps to ensure that users know what they are signing up for.

Why is Apple doing this?

It may or may not be in reaction to Meta’s Muse AI agent, which was accused of reading a journalist’s private messages without permission — a claim Meta denies. 

But even if it is not a reaction to that, the move attempts to put additional obstacles in place to prevent users from casually giving AI agents the power to ransack their private data when they give them Full Disk Access without fully understanding the consequences of doing so.

What Apple said

Here’s what Apple said in a note on its developer website:

“We give developers powerful APIs to build incredible capabilities into their apps for Apple products, backed by a set of controls designed to protect users’ private data. Full Disk Access largely sidesteps these controls in order to allow backup apps to function properly on the Mac. Some developers are using Full Disk Access in ways that could put users at risk, exposing everything on their systems—including files, mail, messages, and even browsing history—without users’ full knowledge and understanding. For communication apps, this can also compromise the privacy of the people users are communicating with.

“Going forward, we will introduce additional controls to ensure that users who genuinely wish to grant an app this extraordinary level of access can only do so with very explicit user action. Addressing this is critical. As AI agents become increasingly capable and autonomous, the risks associated with this level of access will grow substantially. We are committed to ensuring users clearly understand these risks before granting such access, so they can make informed decisions about their own data and privacy.”

The note makes it quite clear that Apple is doing this in reaction to the real and present danger that unconstrained AI places on security systems everywhere. 

Accident, or design?

After all, for every denied instance in which Meta’s Muse may, or may not, have surveyed private messages, there are now many incidents in which some “rogue” AI has “escaped” to do some kind of harm.

Except it’s quite easy to think these incidents are not really escapes, isn’t it? 

If you do, then this is AI doing precisely what it’s designed to do. 

Rather than railing at Apple, developers and critics should focus on why this change has been put in place. It should be recognized as another of the huge “benefits” most humans are already experiencing at this stage of AI disruption.

It’s a benefit to accompany hyper-inflated memory prices on consumer electronics costs. It’s a benefit that flows with the energy and water price increases we are seeing as AI data centers consume more of both, even as inventors of this tech warn that what they have invested hundreds of billions of dollars in poses an “existential threat” to humanity.

Sure, AI can and does release positive consequences, and I celebrate that, but that doesn’t give it a pass on its damage and risk, particularly existential risk.

Obsolete software

“Redefining” that risk is perhaps why Anthropic co-founder Christopher Olah visited Pope Leo XIV to convince people around the head of the Catholic church that AI can be considered conscious. 

One way to see that argument is that AI is not really an existential threat to humanity if you redefine it as some kind of evolution toward a new super race. It becomes a painful but necessary step toward the next phase of humanity, even if that does sound rather messianic (some say fascistic, as Gil Duran explains).

Thankfully, the Pope didn’t buy it. “Algorithms lack the spark of humanity. For this reason, the Church wishes to renew an alliance with artists and cultural institutions to safeguard our humanity,” he wrote in a recent declaration concerning the impact of AI on creative arts.

If I’m honest, and I do try to be, developers and critics attacking Apple for its decision to lock down this aspect of the Mac experience are focused on the wrong target. You need to reconsider who to blame.

For the many

It’s time, urgently time, for people in tech to get back on the road to what makes it great, which is now and always has been what results from the marriage of technology and liberal arts. AI is not conscious. AI has no moral soul. 

With that in mind, it’s appropriate to ensure that humans have informed agency before they provide AI with access to their data. Religions claim that divinity gave us free will. Do you think AI and the billionaires who own it want us to keep that gift? 

Now please subscribe to my daily, human-curated Apple-related news headline feed at The Core, or follow me on BlueSky, LinkedIn, or Mastodon.

Source:: Computer World

By Darius Popa Elon Musk said Tesla’s robotaxis are still working on spotting animals that blend into the road at night, describing the problem as grey kittens on grey tarmac, as Austin’s hours moved to 11pm from 10pm. The EU’s Technical Committee on Motor Vehicles votes on bloc-wide approval of the same camera-only sensor suite on 6 October. […] This story continues at The Next Web

Source:: The Next Web

By Darius Popa China’s industry ministry and six other agencies set 2030 as the date for the first large-scale use of all-solid-state batteries, though CATL’s chairman rates the technology four out of nine and calls million-vehicle use before 2030 very unlikely. ProLogium’s Dunkirk plant, the largest new European cell project since Northvolt went bankrupt, is staged at 0.8 […] This story continues at The Next Web

Source:: The Next Web

By Ana Maria Constantin Ukrainian President Volodymyr Zelensky has asked Donald Trump to sanction the Russian and Chinese companies building Russia’s answer to Starlink, the Financial Times reported. He has raised it with Trump several times, including at a recent meeting in New York. Ukrainian news agency UNN cited those details from the FT report. A network for the front line The […] This story continues at The Next Web

Source:: The Next Web