While 75% of partners see AI as essential, adoption is low. The primary barriers are not just talent shortages, but also managing customer expectations, translating AI into specific business value, and overcoming end-customer concerns about trust, transparency, and control over AI-driven outcomes.

Many AI implementation projects are being paused or canceled due to a lack of immediate ROI. This reflects Amara's Law: we overestimate technology in the short term and underestimate it long term. Leaders must treat AI as a long-term strategic investment, not a short-term magic bullet.

The current AI hype cycle is shifting from selling a futuristic vision to demonstrating tangible value. This mirrors the early adoption phase of SaaS, where customer proof, community validation, and clear ROI were essential to cut through the noise and drive enterprise adoption.

Despite significant promotion from major vendors, AI agents are largely failing in practical enterprise settings. Companies are struggling to structure them properly or find valuable use cases, creating a wide chasm between marketing promises and real-world utility, making it the disappointment of the year.

Marketers observe a significant disconnect between the sophisticated AI workflows discussed online and the more basic applications happening inside companies, even at the CMO level. This highlights the need for practical, real-world examples over theoretical hype.

Vendors fail to connect with SMBs on AI because their messaging is either too technical and intimidating or too aspirational and fluffy. SMB partners and customers want clarity, not hype. They need simple, concrete use cases demonstrating tangible business value like productivity gains or automation, not visions of futuristic robots.

The bar for new AI products is exceptionally high. Customers expect transformative results, like replacing multiple hires or generating six-figure revenue on day one. Products offering only incremental productivity gains will be ignored by a market flooded with high-ROI options.

Despite ServiceNow's heavy AI marketing push, customers feel overwhelmed by numerous, poorly differentiated offerings like "AI control tower" and "now assist." Buyers are pausing adoption, demanding ServiceNow first demonstrate more value from the core products they already pay millions for before they invest in new, confusing AI add-ons.

The initial 'give me everything' hype cycle for enterprise AI is over. Buyers now demand clear ROI and cost justification. This shift from broad experimentation to budget reconciliation will have significant downstream impacts on the entire AI vendor ecosystem.