Social Selling in these two weeks showed a clear shift from activity-based LinkedIn usage to pipeline-oriented execution. The strongest signals were employee-led influence, sharper buyer intent detection, AI-enabled discoverability and LinkedIn’s move toward creator-marketplace infrastructure. Winning teams are treating LinkedIn less as a publishing channel and more as a revenue system across profiles, creators, executives and sales workflows.

Cannes Lions International Festival of Creativity 2026 reflected a marketing industry moving from AI experimentation toward AI-enabled execution. The core shift was not only technological, but strategic: brands are rebuilding creative workflows, creator partnerships, commerce media models and trust-building mechanisms around measurable growth.

Channel marketing over the past two weeks was shaped by a clear shift from partner relationships to measurable partner operating models. The strongest signals centered on co-sell discipline, marketplace execution, AI-enabled partner workflows, partner data quality and activation paths that turn signed agreements into revenue.

MarTech is moving from tool accumulation toward governed, data-native execution layers. The strongest signals are Databricks CustomerLake, Snowflake and Hightouch activation models, Salesforce and Adobe platform moves, and AI workflows that depend on clean data, clear ownership and measurable outcomes. The market narrative is shifting from buying more software to designing better architecture, orchestration and operating models.

Across the selected LinkedIn activity, GTM shifted from tool-led automation toward a broader redesign of revenue operating models. AI is becoming the infrastructure layer for context, data, workflows and execution, while teams with disciplined GTM foundations are best positioned to turn automation into sustained growth.

Field Marketing is framed less as event management and more as a revenue, data, and relationship engine. The strongest themes are sharper event selection, tighter sales alignment, AI-supported workflows, post-event orchestration, and a renewed premium on human connection as digital channels become noisier.

Fundraising is contracting almost everywhere, but the capital that is moving is moving in fewer, larger checks. Mega funds and first-time specialists are still closing on schedule while the broad middle struggles, and liquidity pressure is pushing LPs toward secondaries, continuation vehicles and independent sponsor deals instead of waiting out the traditional fund cycle. Family offices are behaving less like passive allocators and more like competitors for the same deal flow, and governance and reporting quality are becoming as important to LPs as track record.

Capital is not scarce this cycle, it is just picking favorites. Record global funding, record exit values, and a record concentration of both in a handful of AI names sit alongside a founder-level reality of longer diligence, harder term sheets, and funds that cannot deploy the way they used to. Beneath the headline numbers, the same pattern repeats across fund economics, regional markets, and marquee deals: capital is flowing, but it is flowing toward fewer hands, faster, with less patience for anything that cannot prove it belongs there.

Global M&A activity is running at its strongest pace since the early 2000s, yet the market is not moving as one. Technology is pulling in the most capital while its own dealmakers grow more cautious, private equity lags corporate strategics, and AI is reshaping everything from where deals get done to how due diligence is scoped. Underneath the headline numbers, the same lesson keeps resurfacing across very different deals: preparation and cultural execution, not valuation or strategy, are what separate value created from value destroyed.

Strategy and Consulting face a reckoning as enterprise AI shifts from pilots to infrastructure, even as trade and tax policy move on multiple fronts and CFOs balance rising AI optimism against mounting geopolitical risk.

Private equity's two big stories this period are the same story told twice. Deal volume and fundraising both show a market bifurcating between mega scale and everything else, while AI is doing the sorting: which software companies are defensible, which CFOs get hired, which portfolio companies command a premium multiple. Underneath both trends sits a quieter shift in how value gets created and proven, from EBITDA growth alone toward documented, repeatable performance that survives diligence

Venture funding reached record headline levels, but capital increasingly concentrated around a small group of AI and frontier-technology leaders. The broader market remained selective, with LPs prioritising cash returns, managers testing new fund structures and founders facing tighter access to capital.

Digital construction moved at two speeds this period. One group of firms was still locking down fundamentals: templates, ISO 19650 standards, common data environments. Another had moved past that, treating AI agents and proprietary intelligence platforms as the next competitive battleground. Data centers and hyperscale megaprojects tested both, pushing digital field verification and data governance into practice, while capital moved toward platforms that could integrate the flood of new point solutions rather than add to it.

Industrial AI's center of gravity is shifting from pilots to plumbing. The strongest voices this period converge on a single point: value comes from data governance, contextualization, and IT/OT collaboration, not from bigger models. At the same time, the money is moving fast, headlined by Schneider Electric's $3.1 billion move for Cognite, while a persistent talent and reshoring gap threatens to slow the whole transition down.

Across this edition, the story is platform consolidation. Milwaukee, Hilti, Bosch and DEWALT are each pushing customers toward a single cordless battery ecosystem rather than a single tool, while robotics and digital tracking are moving from pilot to commercial order. Safety programs are shifting from compliance checklists to branded recognition and training partnerships, and distributors across the UK, Ireland, France and Brazil are using live demos rather than catalogues to convert accounts.

Over the past two weeks, digital construction moved from isolated experimentation toward embedded workflows across design, preconstruction, compliance and field execution. Construction-native AI, interoperable data foundations and physical automation gained momentum, while governance and human accountability remained essential for scale.

Manufacturing developments over the past two weeks showed a clear shift from experimentation toward operational deployment. Industrial AI, digital twins and connected factory platforms are increasingly being evaluated through measurable productivity, reliability and business outcomes.

Digital powertools activity centred on cordless platform expansion, safer working environments, and specialist solutions for demanding applications. Manufacturers also strengthened dealer networks, repair services, and hands-on demonstrations to convert technical innovation into measurable customer value. Software, circularity, and workforce development are becoming increasingly important competitive dimensions.

Autonomy is moving from pilot programme to production line across the sector. Ukraine's front line remains the fastest proving ground for drones and electronic warfare, European governments are converting funding announcements into signed programmes, and the corporate layer, from Anduril's Ohio factory to Helsing's eighteen billion dollar valuation, shows capital following the same shift toward software defined, autonomous systems.

Across imaging, surgery, and cardiac care, health tech's center of gravity is shifting from proving that AI works to proving it fits. Vendors are shipping AI into existing clinical workflows rather than beside them, regulators on both sides of the Atlantic are formalizing how AI-enabled devices get monitored after launch, and the biggest technology entrant of the period is a government contract for scheduling and intake, not a diagnostic breakthrough. The throughline: infrastructure, governance, and adoption discipline are becoming the real differentiators, not the algorithms themselves.

Three storylines defined this edition. Quantum computing kept moving from lab curiosity to procurement line item, backed by real hardware milestones, national funding, and a widening gap between Europe's industrial readiness and North America's start up density. Cybersecurity spent the period absorbing what happens when AI operates at machine speed, from autonomous vulnerability chaining to a sandbox escape in an AI coding agent, while regulators moved deadlines from someday to a specific date on the calendar. Enterprise technology leaders, meanwhile, were rebuilding infrastructure and software strategy around portability, sovereign compute, and AI agent governance rather than any single platform bet.

Governments are shifting from regulating frontier AI to owning stakes in it, and the same pattern is playing out one level down, where enterprises are discovering that most of the work in AI transformation has nothing to do with the model itself. Sovereignty, cost, and governance are becoming inseparable from deployment decisions, and the infrastructure underneath agentic systems, from data layers to edge devices, is where a lot of that gets tested first. Across every segment below, the throughline is the same: the technology is outrunning the frameworks built to govern, price, and scale it.

Cloud strategy this period split along two axes: where workloads run and who controls the spend. European sovereignty efforts moved from manifesto to measurable deployment, even as the European Commission's own tender process found no provider has yet achieved full sovereignty. Meanwhile AI's cost curve pushed FinOps out of the tooling conversation and into a governance one, with token spend now treated as an engineering control problem rather than a line item.

Sustainability is moving from a compliance line item to an infrastructure design constraint, as companies rebuild data centers around water and energy limits even as hyperscaler emissions climb and public water claims face legal challenge. Developers are shipping tools that make AI's resource cost measurable, from caching engines to CO2 benchmarks, while regulators debate loosening the reporting rules meant to hold the industry accountable. AI's environmental footprint is now a boardroom question, but across conferences from Munich to Geneva it remains a minority conversation next to the technology's growth.