Marketing technology (martech) has entered a new era defined by AI agents, composable architectures, and the rise of buyer-side AI assistants that are fundamentally changing how customers discover brands and B2B vendors.

Growing consumer adoption of AI tools is positioning AI platforms as an alternative shopping channel—but most AI-driven transactions are still completed on retailer websites.

Retailers faced a challenging year as economic factors, new technologies, and changing consumer behaviors reshaped the landscape. Here are our top five stories from this past year and what they meant to a tumultuous industry.

This year’s Cyber Five brought in record sales, but it’s still unclear how consumer spending will unfold through the rest of the holiday season and into the new year. Shoppers are moving in different directions based on their financial stability, and many are starting their holiday buying weeks earlier. Coming out of the gate with strong value and consistent messaging is paying off early, but brands must keep that energy going as the season stretches and shifts.

Brands and retailers are struggling to keep up with changes to the shopper experience as consumers adopt genAI-powered “click-less journeys.”

Future-proofing against—and capitalizing on—advances in consumer-facing AI will be the overarching theme for retailers in 2026.

Automation, new commerce models, and a fresh generation of consumers are transforming the rules of connection and creativity. Explore the 11 trends shaping the digital future.

A year after enterprise software firms began rolling out AI agents, most tools now look and act alike—creating confusion for companies trying to choose the right solution. And because many rely on the same OpenAI or Anthropic models, their offerings are almost indistinguishable, per The Information. Brands should prioritize AI agents that connect across ecosystems, protect data, and scale smarter instead of locking into one vendor’s walled garden. Doing so builds resilience, flexibility, and trust in an increasingly crowded AI market.

OpenAI’s push into commerce took a major step forward with the launch of in-app shopping on ChatGPT, though it will take time to gain traction as a meaningful retail sales channel.

As shoppers flock to LLM-powered searches to learn more about products and set shopping budgets, Salesforce data reveals new opportunities for brands looking to have a firm hold on their customers' journeys.

Salesforce’s launch of Agentforce 360 is a sign that agentic AI is moving into the marketing stack, signaling that automation is becoming a core capability rather than a future experiment. Agentforce can help CMOs decide how far to push agentic AI across their marketing stack. To move from experimentation to deployment, CMOs should start with focused pilots in high-volume touchpoints like chat or email with clear success metrics, such as resolution time or customer satisfaction.

Airline group Lufthansa plans to cut 4,000 roles by 2030 to boost profitability as it leans into AI adoption. The Germany-based company said most layoffs will be limited to administrative roles as it evaluates what work won’t be necessary in the future. Identifying areas where AI is making work redundant and redeploying or retraining employees to higher-value tasks—rather than hacking away at worker numbers—can preserve institutional knowledge and build trust in the technology’s use across an organization.

OpenAI revised its projected cash burn through 2029 to $115 billion—about 230% higher than earlier estimates. This alteration demonstrates how capital-intensive model training and deployment have become and how far those costs are beyond what traditional startup economics can sustain. These financial forecasts illustrate a ballooning cash burn matched by surging investments and rising revenue expectations. OpenAI might need to explore tactics like affiliate links or in-chat advertising for monetization and added incentives and premium features to convert free users into paying ones.

B2B marketing data spending is rising as marketers prioritize strategies that improve ROI, enable AI, and fuel pipeline growth. Trusted data sources and integrated tools are helping teams optimize segmentation, compliance, and campaign performance.

The news: Amazon Web Services (AWS) will launch an agentic AI marketplace designed to help enterprises browse and install AI agents from a variety of startups from a one-stop shop. Our take: The AWS agent marketplace could become a high-value channel for both discovering and distributing automation tools. Enterprises already on AWS’ platform should consider exploring new agent integrations, while startups have a chance to get in front of decision-makers before the market gets even more crowded.

The news: Amazon CEO Andy Jassy said AI-driven efficiencies will reduce the company’s headcount. “As we roll out more generative AI and agents …we will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” Jassy said in a letter to employees. “In the next few years, we expect that this will reduce our total corporate workforce.” Our take: Companies that pursue an AI-first mission by laying off employees risk lower team morale, a resistance to AI adoption among workers, and damaged consumer trust. Still, Amazon’s scale, deep pockets, and cloud infrastructure dominance may insulate it from backlash or major fallout.

AI can be both sword and shield in layoffs: Businesses are cutting costs and staff while repositioning around AI, which is slashing entry-level opportunities and pushing workers to upskill.

The $8 billion Informatica buy signals a pivot from flashy AI tools to reliable, compliant data—core to scaling enterprise automation without sacrificing transparency.

Retailers and brands are racing to deploy AI across the shopping journey, but trust, quality, and execution will define who wins.

Lightrun isn’t building code—it’s safeguarding it, offering proactive debugging that major players like Microsoft and Salesforce trust to catch AI-generated mistakes before they cause chaos.