Two recent pieces perfectly capture this tension. Tom Fishburne’s Marketoonist cartoon post “Misalignment at Speed” nails the organisational reality, while Scott Brinker’s deep-dive “Build vs. Buy Is the Wrong Question for Martech AI” reframes the technology strategy debate. Together, they offer a timely wake-up call for marketing leaders.

The Marketoonist Warning: AI Speed + Silos = More Noise, Not More Results

Tom Fishburne recently shared a William Blair report describing enterprise AI adoption as “a mile wide and an inch deep.” Nearly every organisation is dabbling, but few have orchestrated it strategically.

He cites a 2025 MIT report showing that 95% of enterprise Generative AI pilots failed to deliver meaningful ROI or scale beyond experimentation. The culprit? Not the tools themselves, but strategic misalignment.

Fishburne quotes Hugh Derrick: when you layer “AI-driven speed” onto misaligned systems, you don’t magically become more effective — you simply get faster at being inconsistent. And in big, complex organisations where 30% of senior leaders already blame silos for productivity stagnation and two-thirds describe their companies as overly complex, that speed just creates more noise.

It’s the classic silo syndrome on steroids. Marketing runs its own AI experiments for content. Sales builds agents for lead qualification. Ops automates reporting. Everyone moves faster, but the left hand has no idea what the right hand is prompting. The result? Fragmented customer experiences, duplicated effort, and zero competitive edge.

Fishburne highlights a truism that AI has not changed: technology doesn’t fix broken structures — it amplifies them.

Scott Brinker’s Insight: Build vs. Buy Is No Longer the Right Question

At the same time, Scott Brinker (chiefmartec.com) dropped a must-read preview of the State of Martech 2026 based on a survey of 208 marketing and martech leaders across ~70 specific AI use cases.

His core argument? “Build vs. buy” is the wrong question. AI has collapsed the cost of custom development so dramatically that the old binary no longer applies. The real pattern emerging is hybrid by design.

Key takeaways from Brinker’s research:

• Multiple solutions in parallel are the norm. Teams use embedded AI in existing SaaS platforms (e.g., your MAP or CRM), adopt specialist AI-native tools for creation tasks (copy, visuals, competitive intel), and build custom agents for proprietary data and processes.
• The stack is stratifying, not consolidating. AI-native tools dominate “creation” layers (prompt-driven ideation). Incumbent platforms own orchestration and execution. Agentic CDP-style platforms are emerging as an alternative layer that reasons directly over your first-party data.
• B2B vs B2C behaviour differs. B2B teams go broad (adopting AI across more use cases because they’re often under-resourced). B2C teams go deep — buying off-the-shelf for 80% of needs but building custom solutions for the 20% that matters most to brand voice, guardrails, and differentiation.

Brinker’s conclusion is liberating: stop obsessing over one-size-fits-all vendor lock-in or heroic in-house builds. Focus on orchestrating a portfolio of capabilities that fits your specific context.

The Real Challenge: Silos Make the Hybrid Strategy Almost Impossible

Here’s where the two pieces collide — and why they matter so much for marketing teams right now.

Marketoonist Fishburne shows us that conventional siloed organisations amplify AI’s downsides. You can’t effectively “orchestrate a portfolio” when departments don’t talk, data is trapped, and strategy is misaligned at the top. Brinker shows us the opportunity: a flexible, layered martech stack that blends buy, build, and embed. But that opportunity only materialises if you first fix the organisational operating system.

In other words, AI capabilities don’t break silos — they make silo problems painfully visible (and expensive).

What Smart Marketing Leaders Should Do Differently

If you’re leading marketing or martech in 2026, here are the practical shifts I’m recommending to my clients:

1. Start with problems, people, and principles (not “AI-first”). Borrow from the Marketoonist’s referenced HBR thinking: be problem-centric, people-first, and principle-driven.
2. Build cross-functional AI governance early. Create a small tiger team (marketing, sales, ops, data) that owns the portfolio orchestration Brinker describes. Don’t let every department run their own experiments unchecked.
3. Adopt a stratified stack mindset. Buy infrastructure and orchestration layers you trust. Use AI-native tools for rapid creation. Build custom agents only where proprietary advantage or brand control demands it.
4. Measure alignment before you measure ROI. Track whether AI initiatives are reducing (or increasing) cross-team friction. If pilots are failing at 95%, the first fix isn’t better prompts — it’s better organisational alignment.
5. Reimagine teamwork, not just tasks. As Ethan Mollick’s P&G study (cited in related Marketoonist posts) shows, AI works best as a teammate. That requires new management structures, not just new tools.

The organisations that win won’t be the ones with the most AI tools. They’ll be the ones that use AI to finally break down the silos that have held them back for decades.

At Mackey Enterprises, we’re helping marketing teams do exactly that — turning AI from a source of noise into a genuine competitive advantage. If your organisation is feeling the pain of misalignment at speed, let’s talk.

What’s your biggest AI challenge right now — the technology, the silos, or the strategy? Drop a comment or reach out. I’d love to hear how you’re navigating the build-vs-buy (or rather, orchestrate-the-portfolio) reality in 2026.

Mitchell Mackey Marketing & Business Optimisation Consultant Hobart, Tasmania | mitchellmackey.com.au Driving B2B success in the AI era.

Here’s a summary of Andrei’s timeline of how we got here:

• 2000s – Demand Waterfall Era
  Gate content, manufacture MQLs, hand off to sales. We bought into the illusion of controlling the buyer journey with predictable stages, turning marketing into a volume game: more MQLs = more revenue.
• 2010s – Marketing Automation & Nurturing
  When MQLs failed to convert, we added drip campaigns and lead scoring. The narrative shifted to “warming” leads—shifting blame to sales if “100-point” prospects didn’t close.
• 2014–2023 – Growth Hacking & Outbound Overload
  Scalability became synonymous with tech-heavy tactics: web scraping, automated cadences, ads + outbound on steroids. Marketing shrank to a pure lead-gen function, losing sight of brand and buyer reality.
• 2023 onward – AI Everywhere
  With CMO tenures dropping and layoffs exposing inefficiencies, AI promises to do more with less: auto-generate content, enrich leads, build workflows overnight. Yet many leaders are now racing to prove they’re “AI-native” out of FOMO—while avoiding the real issue.

The elephant in the room? We’re trapped in a broken system that rewards short-term metrics over long-term strategy. AI isn’t the escape hatch; it’s just another layer of complexity. True survival—and thriving—comes from challenging the status quo: hard conversations with leadership about marketing’s real role, deeply understanding customers and their journeys, and building brands that B2B buyers actively choose.

This is the reset B2B marketers need in 2026. Zinkevich’s core message resonates deeply with what I see in my work: efficiency gains from tools are meaningless without reclaiming marketing as a strategic, full-funnel discipline focused on customer reality, not just pipeline volume.

If you’re ready to move beyond the “lead vending machine” trap and rebuild a more effective, buyer-led marketing engine, I recommend tuning into the conversation Andrei is leading.

Next week (March 24–26, 2026), FullFunnel is hosting the 7th Virtual Full-Funnel Summit—free to attend.

It’s a 3-day virtual event with 15 live keynotes from B2B experts (including Andrei himself and his cofounder Vlad Blagojevic), focused on actionable full-funnel strategies, case studies, and real-world insights for high-ACV, long-cycle B2B companies. No product pitches—just practical advice on aligning marketing and sales for genuine growth.

Save your free spot here: https://fullfunnel.io/summit/

Whether you’re reassessing your martech stack, rethinking ABM in an AI era, or simply tired of short-termism, this summit is a timely opportunity to hear from leaders pushing back against the broken playbook.

What’s one outdated B2B tactic you’re ready to ditch in 2026?

If you’d like to explore how centralised, full-funnel strategies can transform your marketing function, reach out via the contact form or book a call.

The content boom: budgets up, volume surging, AI leading the charge

Content production is accelerating at a pace that’s outstripping expectations, fueled by expanding channels and AI innovations:

• Rising budgets: Over 80% of organizations plan to increase content and creative budgets in the near future, up from 70% in 2024. Notably, 29% expect significant increases, a jump from 19% in 2023.
• Volume explosion: 82% of teams reported higher content output last year, with 27% seeing significant growth. AI is the primary driver, with 75% of professionals saying it has boosted volume—30% significantly.
• Evolving ROI metrics: Success is measured through a mix of engagement (40%), brand awareness (38%), conversions/lead gen (38%), and sales revenue (38%). ROI is improving, with 28% reporting significant gains (up from 19% last year).

Teams with mature workflows are reaping the rewards, being 3x more likely to see substantial ROI. This underscores the need for investments in AI, automation, and centralized systems to handle the surge without sacrificing quality.

Content operations: maturity matters, fragmentation hurts

Operational challenges persist, but top performers are addressing them head-on. Canto’s report highlights persistent pain points like keeping up with content demands (40%) and managing volume (36%), but also shows progress in tech adoption.

• Workflow maturity: Only 43% have advanced, standardized workflows, but these teams report 48% significant ROI increases compared to 0% for those with ad-hoc processes.
• Improvement tactics: 51% are using AI for creation, tagging, and organization; 41% are enhancing cross-team collaboration; and 36% are introducing automation to cut manual work.
• AI’s role in efficiency: Widespread AI users find maintaining brand consistency extremely easy (49% vs. 6-9% for non-users).

High-ROI teams prioritize automation (47%), templates (45%), and asset distribution (33%), proving that streamlining operations directly boosts returns.

Digital Asset Management: centralization is key to avoiding chaos

Fragmented asset storage, a persistent problem, remains a major drag, with most teams using multiple systems like cloud storage (62%) and DAM solutions (47%). The consequences are clear:

Only 35% are very confident employees use up-to-date brand assets, meaning most perceive that colleagues in sales, product management, customer service and the broader marketing team are using dated, often inaccurate materials which exposes their brands to numerous risks.

In contrast, DAM users report smoother operations, and those unifying assets with product content see 4x higher ROI gains.

For product-focused teams, accuracy is critical: 88% struggle with consistency across channels, but centralized approaches reduce duplication and improve access.

Tech stack optimization: closing gaps for better scale

Content teams lose time on manual tasks, with 22% prioritizing AI automation and 21% better search/retrieval. Core capabilities like analytics (43%) and standardized workflows (41%) are established in many organizations, but only 24% have fully optimized stacks.

Teams with strong ROI excel in AI tools (59%), analytics (50%), and automated tagging (42%). As stacks mature, expect more focus on integration to eliminate silos.

AI throughout the lifecycle: from analysis to personalization

AI is embedded across operations, with top uses in performance analysis (41%), SEO optimization (40%), and tagging (39%). High-ROI teams apply it more broadly, especially in personalization (41%) and discovery (43%).

Looking ahead, teams want AI for streamlining reviews (38%), smart search (36%), and reuse recommendations (35%). Adoption is at 77%, with 81% confident in AI’s accuracy for tagging—higher among heavy users.

What this means for your marketing strategy

The report paints a clear picture: success in 2026 hinges on operational maturity. Fragmented systems fuel burnout, waste and magnify risks, while AI-driven, centralized approaches unlock speed, consistency, and ROI. If your team is stuck in manual workflows or siloed assets, now’s the time to audit and optimize.

I help businesses in Tasmania and beyond implement these strategies— from AI integration to DAM setups. If you’re ready to scale your content operations, let’s talk. Download the full Canto report here to dive deeper. Let’s turn these insights into action for your business.

Key takeaways from the piece include:

• Democratization of Building: With AI making creation and automation “free” or low-cost, the real challenge shifts to distribution. As Bodnar puts it, “When building is free, distribution becomes everything — and that means more money, attention and energy will flow here than ever.” This signals a surge in investment toward marketing strategies that cut through noise and capture audience attention.
• Pivoting to Complexity: Initially focused on simplifying paid ads for smaller users, Bodnar’s team adapted by developing sophisticated AI workflows for large ad agencies managing hundreds of accounts. This highlights AI’s role in scaling operations but underscores the enduring need for human oversight—especially in high-stakes areas like budget allocation on platforms such as Google Ads or Meta, where errors can be costly.
• Human-AI Synergy: While AI empowers non-experts to handle end-to-end marketing workflows, Bodnar and commenters emphasize the risks. Non-specialists might miss nuances or errors in AI suggestions, reinforcing the value of expert-guided AI systems for trust and performance.

This evolution in martech points to a future where AI agents handle routine tasks, freeing marketers to focus on strategy, storytelling, taste, and building genuine consumer trust. However, it also warns of potential disruptions for traditional agencies and tools that don’t adapt quickly.

Bodnar’s experience is a timely reminder for marketing professionals: Embrace AI as an amplifier, not a replacement, and prioritize distribution in an era of abundant creation. For those in the sector, it’s worth checking out the full article on X for deeper insights into building resilient AI-driven strategies.

(Originally shared by @irabukht on X: https://x.com/irabukht/status/2025846968245948795)

SaaS spending hits highs amid AI volatility

One of the standout revelations is the continued growth in SaaS expenditures. Large organizations are now averaging $55.7 million in annual SaaS spend, an 8% increase year-over-year. This uptick isn’t just from adding more tools; it’s largely fueled by AI integrations and evolving pricing models. AI-native applications have seen a massive 108% surge in spend overall, skyrocketing to 393% for big enterprises. Meanwhile, the broader AI category has exploded with 181% growth in usage, making it the fastest-expanding segment in the dataset.

However, this growth comes with challenges. 78% of IT leaders reported unexpected charges from AI features or consumption-based pricing, while 61% had to cut projects due to these unplanned costs. These figures underscore the need for robust governance to manage volatility, as rising costs can erode budgets and weaken negotiation positions during renewals.

Stabilizing portfolios with a focus on AI embedding efforts.

Gone are the days of unchecked SaaS sprawl. Rather than expanding through new acquisitions, growth is happening within existing tools via AI embeddings, tier upgrades, and usage-based pricing. This shift signals a maturation in SaaS management, where “SaaS velocity”—the rapid entry and exit of applications—demands stricter intake processes and clear ownership to mitigate risks.

New tools, such as the Digital Sales Room (DSR) Trumpet, are being introduced, but at the expense of legacy tech. In 2025, organizations added 34% new tools to their tech stacks. Yet overall stack size grew only 11% — 305 total apps on average, up from 275.

AI’s transformative role in SaaS

AI isn’t just a buzzword; it’s fundamentally altering the SaaS ecosystem. According to the report, 64% of SaaS companies are embedding AI as a supporting feature, with 36% making it core to their offerings. An impressive 92% have either launched or plan to introduce AI capabilities. This proliferation is rewriting pricing structures, moving from traditional seat-based models to token, action, or usage-based charges that can introduce mid-contract surprises.

Looking ahead, the report predicts AI will become the most expensive “invisible worker,” automating tasks but creating unmanaged spend. Usage-based pricing will expose low-value AI implementations, accelerating consolidation, and a “value crisis” will emerge, where spend must be justified by measurable outcomes.

Security risks and the imperative for governance

With AI’s rapid integration comes heightened security and financial risks. Hidden AI features in familiar tools can amplify exposure before governance catches up. The report emphasizes that without mature practices—like full visibility, cross-functional alignment between IT asset management (ITAM) and FinOps, and disciplined renewals—organizations are vulnerable to greater volatility and lost control.

Benchmarks and actionable recommendations

Zylo’s benchmarks, grounded in hard data rather than surveys, offer a roadmap for success. Companies with strong SaaS management programs are better equipped to handle AI-driven changes, improving forecasting and renewal outcomes. Key recommendations include:

• Implementing programmatic management to adapt to dynamic pricing.
• Aligning ITAM and FinOps for better usage insights and cost predictions.
• Tying AI expenditures to business value during evaluations and renewals.
• Prioritizing intake discipline to manage the accelerating churn in SaaS portfolios.

As we head further into 2026, trends like AI volatility, faster application lifecycles, and higher-stakes renewals will make SaaS management a core competency across teams.

Optimizing Your SaaS Strategy

AI is clearly both an opportunity and a challenge in the SaaS world. For businesses looking to thrive, investing in governance and visibility isn’t optional—it’s essential. If you’re navigating these complexities in your marketing or operational strategies, let’s connect. .

The 2026 edition, marking its 10th anniversary, cuts through market noise to highlight converging innovation platforms that are accelerating step-function changes in productivity, capital allocation, and global growth. It’s not just a forecast; it’s a framework for understanding how these technologies are scaling from niche ventures to mainstream forces. As ARK puts it, “the future doesn’t arrive all at once. Those who recognize it early have the opportunity to Own What’s Next.”

Key Messages from Big Ideas 2026

Drawing from ARK’s research across public and private markets, the report explores 13 interconnected “Big Ideas” spanning AI, blockchain, space exploration, robotics, energy, and biology. At its core is “The Great Acceleration,” authored by the firm’s Chief Futurist Brett Winton, which positions AI as the central dynamo igniting five major innovation platforms: AI, Public Blockchains, Robotics, Energy Storage, and Multiomics. Here are the standout insights:

Technological convergence is driving exponential growth: Disruptive technologies are no longer siloed—they’re intermeshing at an unprecedented rate. The report notes that Convergence Network Strength, a metric tracking how these platforms catalyze each other, surged 35% in 2025. AI remains the key enabler, but robotics and energy storage are emerging as critical catalysts. For instance, reusable rockets could deploy AI chips in orbit to overcome earthly constraints on cloud computing, potentially boosting demand for space launches by 60x. Meanwhile, multiomics data shared via digital wallets could fuel neural networks to develop precision therapies for rare diseases. Multiomics isn’t just more data—it’s smarter, interconnected data that turns complex biology into actionable insights, much like how AI turns raw compute into intelligence.

• Unprecedented investment cycles ahead: The world is entering a massive technology investment wave, with capital expenditures as a percentage of GDP poised to rival historical booms like electrification or automobiles. ARK forecasts that innovations in AI data centers, robotaxis, and space-based compute could drive this surge, far exceeding consensus expectations. Historical parallels show how past tech shifts— from railroads to software—transformed economies, and today’s convergence could amplify that impact.
• Profound macroeconomic implications: Each platform has the potential to deliver structural boosts to global GDP. A compelling example: humanoid robots in the home. Currently, only about $2,600 of the average $68,000 in annual home upkeep contributes to GDP. A single household robot could add $62,000 per year by monetizing unpaid labor. If adopted in 80% of U.S. households over five years, this could accelerate GDP growth from 2-3% to 5-6% annually. Overall, ARK projects that capital investments in these platforms could add 1.9 percentage points to annualized real GDP growth this decade, with realized growth potentially exceeding forecasts by over 4 points as returns on invested capital soar.
• From experimentation to scale: The report delves into specific Big Ideas, such as AI Infrastructure (scaling neural networks), Bitcoin and Tokenized Assets (building a digital monetary ecosystem), Multiomics (advancing biology through data), Reusable Rockets (enabling space-based AI), and Autonomous Logistics (revolutionizing transportation). These aren’t isolated trends; their interdependence—e.g., stablecoins enabling AI agents to direct real-world resources—could redefine competitive advantages across industries.

ARK emphasizes that while these opportunities are immense, they come with uncertainties. Investors should approach with a cross-sector lens, understanding regulatory, political, and market risks. The report serves as an educational tool, not investment advice, reminding us that past performance doesn’t guarantee future results.

In a world where innovation is accelerating faster than ever, ARK’s Big Ideas 2026 offers a clear-eyed view of what’s on the horizon. For those in Tasmania and beyond looking to stay ahead, it’s essential reading. You can download the full report from ARK Invest’s website to dive deeper. What are your thoughts on how these trends might shape our economic future?

What is Martec’s Law?

At its core, Martec’s Law observes that technological progress follows an exponential curve—think Moore’s Law, where computing power doubles roughly every two years, or Metcalfe’s Law, which shows how network value grows exponentially with connections. Social media’s rapid evolution is another prime example: what started as simple platforms has exploded into complex ecosystems that reshape how we communicate and market.

In contrast, organizations evolve much more slowly, on a logarithmic scale. This isn’t just about size or bureaucracy; it’s rooted in human factors like established processes, cultural inertia, incentives, and the sheer effort required to shift behaviors. Larger teams amplify this resistance, making change feel like pushing a boulder uphill. Without strong leadership, stagnation becomes the norm.

Brinker calls this dynamic “the great management dilemma of the 21st century”.

Implications for Marketing and Beyond

For marketers, this law is especially relevant in the martech space, where tools and platforms multiply at a dizzying rate. It’s not just about adopting the latest AI-driven analytics or automation software—it’s about integrating them into your team’s workflow without causing disruption. The risk? Overwhelmed employees, half-baked implementations, and missed opportunities as competitors who bridge the gap pull ahead.

But it’s not all doom and gloom. Brinker emphasizes that even the best-led organizations can’t match technology’s pace outright. Instead, the key is strategic selection: consciously choosing which changes to embrace and which to ignore, aligning them with your broader business goals. As he draws from A.G. Lafley’s Playing to Win, strategy is about making tough choices—what’s “in” (the red area) and what’s “out” (the blue).

How to Bridge the Gap

To make Martec’s Law work for you, focus on absorption as much as adoption. This means:

• Strategic Prioritization: Evaluate tech changes against your organization’s mission. Not every shiny new tool deserves a spot in your stack.
• Cultural Integration: Go beyond installation—invest in coaching, training, and inspiring your team. Educate on why the change matters, nurture buy-in, and elevate those who champion it. A experienced consultant once recommended to myself that for every $1 committed to software licensing/subscribing, $3 should be allocated to training and change management.
• Proactive Leadership: Anticipate the gap and plan for it. In marketing, this could involve piloting martech tools in small teams before scaling, ensuring they enhance rather than hinder creativity.

I’ve seen businesses thrive by applying these principles. For instance, a mid-sized firm might skip the hype around every new AI platform and instead double down on data privacy tech that aligns with their customer trust strategy.

If you’re grappling with martech overload, Martec’s Law offers a roadmap. It’s a reminder that thoughtful adaptation beats frantic chasing. Check out Brinker’s original article for a deeper dive, and let’s discuss how this applies to your organization—drop a comment below or reach out via the contact form.

Originally inspired by Scott Brinker’s article on chiefmartec.com.

Key Highlights from Forrester’s 2026 Predictions

Forrester outlines five pivotal trends that will shape B2B operations this year, all centered on “The Race to Trust and Value.” Here’s a what they mean for marketing, sales, and product teams:

• Governed AI for Smarter Outcomes: While ungoverned generative AI could lead to significant costs, proactive governance opens doors to efficiency. With 75% of sales reps already using AI tools, empowering your team with AI literacy can prevent pitfalls and value through better decision-making.
• Human Expertise as a Competitive Edge: Buyers are craving deeper validation beyond AI—30% viewed genAI as meaningful in 2025, but human interactions with product experts top the list for trust. This shift highlights the power of upskilling your teams to deliver personalized insights, fostering stronger buyer relationships from early stages to post-sale success.
• Influencer Relations as Growth Levers: A huge 75% of B2B enterprises plan to boost budgets here. As buying networks expand, influencers like analysts and experts become key to building trust. Integrating them into your go-to-market (GTM) strategy—via social amplification and endorsements—can elevate proof-of-success over brand reputation, driving measurable impact.
• AI Agents Revolutionizing Payments: Expect AI agents in one-third of B2B payments, streamlining complex workflows like invoicing and trade credit. Vendors like Basware and Coupa are leading the charge, promising higher automation and efficiency—perfect for Australian firms dealing with diverse supply chains.
• Agent-Led Negotiations for Dynamic Deals: 20% of sellers will engage AI buyer agents in quotes, turning negotiations into data-driven, compliant opportunities. This evolution from static pricing to agile interfaces means suppliers with strong AI partners can protect margins while adapting to buyer demands.

These predictions underscore a market where clarity, accountability, and human-AI synergy win big. In volatile times, they’re your roadmap to turning rapid change into sustainable advantage.

Activation guidance

Ready to put Forrester’s insights into action? Here’s practical advice for B2B leaders in Tasmania and beyond:

1. Build AI Governance from the Ground Up: Democratize AI education—train teams to spot bad outputs and integrate governance into commercial apps. Start small: Audit your current tools and invest in “AI intelligence quotient” workshops to boost confidence and reduce risks.
2. Elevate Human Touchpoints: Prioritize product experts and customer success teams early in the buyer journey. Upskill them to handle complex queries, ensuring your offerings meet real needs. This not only validates AI insights but builds lasting trust.
3. Strategize Influencer Engagement: Shift from tactical PR to integrated GTM. Expand your signals to include influencer activity—track commentary and endorsements. Align budgets with performance metrics to see ROI in buyer discovery and conversions.
4. Embrace AI Agents in Workflows: For payments and negotiations, partner with agentic AI vendors. Assess your invoicing and procurement processes for automation potential, starting with pilot programs to scale efficiencies without disrupting operations.
5. Prepare for Buyer Evolution: Equip sales teams with AI agents for counteroffers, focusing on margin protection and compliance. Collaborate with in-house engineers or trusted partners to stay agile in a market where 61% of buyers use genAI for purchasing.

By prioritizing trust and value—as Forrester advises—you’ll position your business for growth in a buyer-empowered world.

For more on how digital marketing can amplify these strategies, from AI-optimized content to influencer campaigns, let’s chat. Connect via mitchellmackey.com.au/contact. Here’s to a prosperous, high-impact 2026!

Mitchell Mackey | Digital Marketing Strategist | Hobart, Tasmania Driving B2B Success in the AI Era

Leading marketing technology consultant Scott Brinker, of Martec, says we marketers are all facing variations of the following challenges:

Subscription Fatigue: Companies are overwhelmed by the sheer number of SaaS subscriptions. Managing dozens of tools—each with its own pricing tier—creates complexity and cost creep. In Martech, this is acute, as teams juggle platforms for email, social, SEO, and more.

Diminishing Returns: Many SaaS tools promise innovation but deliver incremental improvements. Marketers often find overlapping features across platforms, leading to redundancy and inefficiency.

Integration Challenges: The dream of seamless SaaS ecosystems often falls short. Disparate tools require complex integrations, leading to data silos and workflow bottlenecks.

Market Saturation: The martech landscape is overcrowded. New entrants struggle to differentiate, and consolidation (e.g., Zuora’s $1.7B acquisition by Silver Lake and GIC in 2024) signals a maturing market.

Economic Pressures: Complex economic macros and tighter budgets in 2025 are pushing companies to scrutinize SaaS spending. CFOs are questioning the ROI of tools that don’t deliver measurable impact.

The Rise of SaaS

SaaS emerged as a game-changer in the early 2000s, driven by pioneers like Salesforce. By delivering software over the internet, SaaS eliminated the need for costly on-premise installations, enabling businesses to scale quickly and pay only for what they used. In Martech, this fueled an explosion of tools, covering everything from CRM to analytics and automation. The low barrier to entry empowered startups and enterprises alike, democratizing access to cutting-edge technology.

The appeal was clear:

• Cost Efficiency: Subscription models spread costs over time.
• Scalability: Tools could grow with a company’s needs.
• Accessibility: Cloud-based platforms allowed global, real-time collaboration.

For marketers, SaaS meant agility. Teams could deploy tools like HubSpot or Marketo to orchestrate campaigns, analyze data, and personalize customer experiences without heavy IT involvement.

The Fall of SaaS?

However the SaaS trajectory is shifting. Brinker argues that we’re entering a “post-SaaS” era, where the model evolves or gives way to new paradigms. Key trends include:

• Consolidation and Platforms: Mega-platforms like Salesforce and Adobe are absorbing smaller players, creating all-in-one suites. This reduces the need for multiple subscriptions but risks vendor lock-in.
• AI-Driven Automation: AI is reshaping martech, with tools embedding generative capabilities to automate content creation, analytics, and personalization. This could reduce reliance on specialized SaaS tools.
• Open-Source and Hybrid Models: Businesses are exploring open-source alternatives or hybrid solutions (e.g., self-hosted SaaS) to cut costs and gain control.
• Usage-Based Pricing: Some SaaS providers are shifting to pay-per-use models, aligning costs with actual value delivered.

What This Means for Marketers

For Australian businesses, particularly those leveraging martech, the evolving SaaS landscape demands a strategic rethink:

• Audit Your Stack: Review your SaaS subscriptions to eliminate redundancy. Tools like our consulting services can help optimize your martech stack.
• Prioritize Integration: Invest in platforms that integrate seamlessly or leverage APIs to connect your ecosystem.
• Embrace AI: Adopt AI-powered tools to streamline workflows and reduce dependency on multiple SaaS products.
• Negotiate Contracts: With market consolidation, negotiate better terms with SaaS providers to maximize value.

Looking Ahead

SaaS transformed martech, but its challenges—cost, complexity, and saturation—are undeniable. As Brinker notes, the future lies in smarter, more integrated solutions that prioritize outcomes over subscriptions. At MitchellMackey.com.au, we’re committed to helping Australian businesses navigate this shift, ensuring your martech investments deliver real results.

This post is adapted from Scott Brinker’s insights in the State of Martech 2025 report, co-authored with Frans Riemersma. For the full report and more Martech insights, visit chiefmartec.com or download the report at content.martechday.com/state-of-martech-2025.pdf.

Brinker’s key theme is that marketing has become a technology-powered discipline, and therefore marketing organizations must infuse technical capabilities into their DNA. I agree.

The product manager—a bright, young, and refreshingly candid voice in the martech world—shared an observation, gained from many formal and informal discussions with senior executives across the world, that was not surprising and yet still shocking. Despite decades of so-called “lessons learned,” and the explosion of sophisticated sales and marketing technologies, the fundamental rift between sales and marketing teams remains stubbornly in place at all too many big and small companies.

The arguments are eerily familiar to anyone who’s been in B2B long enough:

• Marketing complains that sales doesn’t convert the leads they’ve worked so hard to generate.
• Sales counters that marketing doesn’t deliver enough high-quality leads worth pursuing.

These debates were raging decades ago. They’re still raging today.

The truth—then and now—is that neither side is entirely right or wrong. The real issue is that too many organisations treat sales and marketing as separate, even competing, functions rather than two halves of the same revenue engine.

As my new friend in martech product management highlighted, no ABM platform, no AI-powered targeting tool, no shiny piece of martech will magically bridge this divide. Technology can enable better alignment, but it can’t create it.

What’s required is genuine, consistent collaboration—not just between department heads, but all the way down to the front lines. That means:

• Talking regularly—not just at quarterly reviews, but in weekly syncs and shared planning sessions. Most do this, but few do it well.
• Agreeing on common goals—clear revenue targets, shared definitions of a qualified lead, and mutual accountability for results. Common goals are, of course, common sense, but this remains a scarce commodity.
• Embracing one unified scoreboard—so that both sales and marketing are working to the same numbers, in real time, without the selective reporting that fuels mistrust. Separate reporting and tracking processes and systems are almost guaranteed to generate friction.

Genuine collaboration is simple in concept, hard in practice, and absolutely essential. The most advanced ABM platform in the world—contact-level or otherwise—will fail in an environment where sales and marketing remain siloed. But when the two teams align on purpose, process, and performance measurement, technology becomes a force multiplier rather than a false promise.

If you’re investing in ABM, don’t just evaluate the tool. Evaluate your organisation’s willingness to collaborate—because without that fundamental commitment, you’re just buying another piece of tech for the shelf.