惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Apple Machine Learning Research
Apple Machine Learning Research
T
Tailwind CSS Blog
月光博客
月光博客
爱范儿
爱范儿
有赞技术团队
有赞技术团队
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
aimingoo的专栏
aimingoo的专栏
GbyAI
GbyAI
腾讯CDC
The Cloudflare Blog
人人都是产品经理
人人都是产品经理
MongoDB | Blog
MongoDB | Blog
Microsoft Azure Blog
Microsoft Azure Blog
IT之家
IT之家
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
云风的 BLOG
云风的 BLOG
U
Unit 42
博客园 - 三生石上(FineUI控件)
A
About on SuperTechFans
N
Netflix TechBlog - Medium
Google DeepMind News
Google DeepMind News
雷峰网
雷峰网
L
LangChain Blog

informationweek

2026 tech company layoffs How Sedgwick scaled AI in legacy claims workflows InformationWeek Podcast: CTOs on using AI in regulated spaces How top CIOs are measuring the real ROI of IT automation What AI must learn from Roosevelt, conservation and 1929 Experian's chief innovation officer gleans AI gains with startup collab ETS CIO on competing with AI startups 'running with scissors' Before the next VMware: How CIOs prepare for vendor shocks The strategic alignment powering cyber-resilient organizations The AI infrastructure bottleneck is becoming a CIO problem InformationWeek Podcast: CTOs on reining in rogue AI agents Workplace equity in the age of AI Why and how to implement an AI asset rationalization strategy Why companies are shifting toward private AI models AI agents in automation: When to build, when to buy Navan CTO AI on trial: The Workday case that CIOs can The AI infrastructure boom is coming for enterprise budgets How CIOs can manage LLM costs: A practical guide InformationWeek Podcast: How CTOs balance AI and their teams Whirlpool, Duke Energy, Cleveland Clinic CIOs on scaling AI Where CIOs get stuck rebuilding the enterprise: What 'Rewired' reveals As AI makes projects harder to track, will CIOs need new controls? Why disaster recovery plans fail in geopolitical crises A silent erosion of enterprise AI by data poisoning Priceline CTO prioritizes engineers able to 'hold a room and a roadmap' InformationWeek Podcast: When CTOs need to restart IT projects Wayfair CTO maps agentic path across digital and brick-and-mortar commerce The AI contract gaps the Google-Pentagon deal just made visible Non-human identity sprawl is agentic AI's real risk
What CIOs miss when buying vertical SaaS software
John Edwards · 2026-05-08 · via informationweek

When CIOs search for the best vertical SaaS software for their organization, they look for the key attributes that will meet their specific needs. Yet subtle differences among similar SaaS offerings can lead to acquiring a product that matches their precise needs or one that fails to meet expectations.

Here's a look at the top vertical SaaS software mistakes and misconceptions and how to avoid them.

Understand any trade-offs

"What many CIOs overlook when purchasing a vertical SaaS offering is that they aren't only procuring a specialized application, but also accepting the vendor's underlying data architecture, workflow processes and -- increasingly -- the artificial intelligence layer," said Mahesh Juttiyavar, CIO at Mastek, a digital and cloud transformation firm. "While the product's accelerated time-to-value seems tempting, the ease of implementation comes with trade-offs."

Juttiyavar added that CIOs also need to pay close attention to how well data governance will be ensured, how flexible the workflow configuration will be, and how the chosen solution can be made compatible with the rest of the enterprise stack.

Related:Why build vs. buy doesn't fit modern IT systems

Establish frameworks for data governance

CIOs often underestimate how critical data quality, governance and portability are when evaluating vertical SaaS platforms, focusing instead on surface-level features and speed to deployment, said Steve Karp, CIO of Unanet, a firm offering project-based ERP and CRM solutions.

IT leaders should establish, socialize and enforce strong data governance practices, processes and procedures, he added. They should also focus on creating a centralized, integrated and secure data repository to serve as the single source of truth for the business, one that's readily accessible to enterprise AI and analytics tools and to relevant people across the organization.

Assess AI readiness

CIOs need to assess the interfaces that enable interaction with AI, including conversational and generative experiences, said Mark Smith, a partner and chief software analyst at technology research and advisory firm ISG. "These interfaces determine whether the application can support modern workforce engagement and integrate with enterprise AI strategies," he said.

Smith added that feature- and functional-fit answer only whether an application meets current business needs. "CIOs now need to understand how the application operates as a platform -- including its data architecture, governance model and the ways it enforces policies and rules that underpin industry-specific processes," he said.

Related:Why value-based pricing is inevitable

Consider visibility and accountability

One of the most common mistakes CIOs make when dealing with vertical SaaS applications is a lack of visibility and accountability, according to Aimen Hallou, CTO at web intelligence solutions developer Floxy. "When AI models, automation rules and workflow logic all reside inside third-party environments, CIOs don't know how decisions are made, optimized or audited." Once a system is deployed for several years, recovering the company's workflow logic may become problematic due to a heavy reliance on proprietary workflows and decision rules rather than modular components that can be controlled in-house.

Does the tool fit your needs?

CIOs frequently evaluate a SaaS offering against the problem it solves in isolation and miss the cost of the silo it creates, said Shams Chauthani, CTO at Tempo Software, a cloud-based developer of strategic portfolio management solutions.

A vertical tool might be the best answer for one team's workflow, but it also needs to fit in with the broader software portfolio and the needs of the organization at large. The real question shouldn't be, "does this tool solve the team's problem?" Chauthani said. "It should be, does this make the organization smarter, or just one department faster?" 

Related:The rise of purpose-built software

The hidden cost of technologies that don't integrate tends to materialize 12 to 18 months in, when it becomes apparent that the data is trapped in multiple tools that can't talk to each other, Chauthani warned.

Plan for an acceptable exit strategy

Before deploying a new SaaS platform, CIOs should consider what happens when the relationship ends, as it inevitably will, explained Moe Rosenfeld, CIO at document management services firm eCopier Solutions. How will you get your data out, in what format will it arrive, and how long will it take?

"I've watched organizations realize mid-migration that their data was effectively held hostage in a proprietary schema nobody outside the vendor understood," he said. "That issue should be answered on page one of every evaluation, not buried in a legal review after you've already signed."

About the Author

John Edwards

Technology Journalist & Author

John Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.