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

V
Vulnerabilities – Threatpost
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
Engineering at Meta
Engineering at Meta
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Blog — PlanetScale
Blog — PlanetScale
aimingoo的专栏
aimingoo的专栏
雷峰网
雷峰网
Microsoft Azure Blog
Microsoft Azure Blog
V
Visual Studio Blog
F
Fortinet All Blogs
C
CERT Recently Published Vulnerability Notes
Spread Privacy
Spread Privacy
月光博客
月光博客
L
LINUX DO - 热门话题
C
Cisco Blogs
P
Proofpoint News Feed
C
Cyber Attacks, Cyber Crime and Cyber Security
爱范儿
爱范儿
B
Blog
P
Privacy International News Feed
Know Your Adversary
Know Your Adversary
The Cloudflare Blog
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Cyberwarzone
Cyberwarzone
J
Java Code Geeks
罗磊的独立博客
D
Darknet – Hacking Tools, Hacker News & Cyber Security
Cisco Talos Blog
Cisco Talos Blog
T
Tor Project blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
博客园 - 司徒正美
酷 壳 – CoolShell
酷 壳 – CoolShell
Simon Willison's Weblog
Simon Willison's Weblog
量子位
H
Help Net Security
The Register - Security
The Register - Security
L
LangChain Blog
GbyAI
GbyAI
Vercel News
Vercel News
S
Schneier on Security
T
Threatpost
T
Threat Research - Cisco Blogs
有赞技术团队
有赞技术团队
Y
Y Combinator Blog
阮一峰的网络日志
阮一峰的网络日志
C
Check Point Blog
MongoDB | Blog
MongoDB | Blog
Recorded Future
Recorded Future
G
GRAHAM CLULEY
MyScale Blog
MyScale Blog

informationweek

2026 tech company layoffs 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 What CIOs miss when buying vertical SaaS software 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 Anthropic's Mythos forces a rethink of vulnerability management Outsourcing contracts weren't built for AI. CIOs are renegotiating now The AI spend hangover companies didn't plan for The power of CIO networking in the competitive AI world Why CIOs see AI projects stall: Speed without structure kills scale IT leaders should never let a good crisis go to waste SFO's digital twin maps airport operations from the curb to takeoff CIOs caught in the middle as AI startups disrupt vertical Saas Submit an IT Leadership column to InformationWeek Podcast: Rightsizing AI frameworks to avoid failure modes The invisible labor crisis inside IT: AI work the org chart can't see Why AI teams treat training data like capital Ask the Experts: How CIOs can identify and overcome cultural barriers to innovation Nobody told legal about your RAG pipeline -- why that's a problem Meta's new 'AI Zuckerberg' is a mirror for every C-suite Will the music stop for AI's funding dance? Rethink tech talent: Local is the smartest play for IT InformationWeek Podcast: Catching errors in AI-powered code CIOs can combat talent scarcity with AI-augmented leadership -- Gartner How Bellevue, Wash., is applying AI to streamline a broken permitting process Ignore the hype: Smarter tech bets at speed of change Who controls the fix? Colorado's repair fight tests CIO power Ask the Experts: The red flags that signal an AI project isn't worth pursuing The hidden high cost of training AI on AI Red Hat's Marco Bill: Resource control is key for AI sovereignty InformationWeek Podcast: New IT architecture, cloud, edge and AI Enterprises need Tier 1 provider relationships to deliver on AI How CIOs run and rebuild the business at the same time in the AI era It's not your tech stack, it's your structure -- fix it Confidential computing resurfaces as security priority for CIOs FinOps: Helpful tool, or a cloud control placebo for CIOs? Cleveland's open data overhaul: From sticky notes to public dashboards As Microsoft expands Copilot, CIOs face a new AI security gap Why build vs. buy doesn't fit modern IT systems InformationWeek Podcast: Is quantum computing slumbering? Your AI vendor is now a single point of failure Vibe coding: Speed without security is a liability A practical guide to controlling AI agent costs before they spiral AI fuels a new wave of technical debt The sunsetting of Sora: A hard lesson in AI portfolio resilience HP pushes broad internal AI use after early productivity gains Why value-based pricing is inevitable InformationWeek Podcast: Safeguarding ecosystems from outsiders Why AI scaling is so hard -- and what CIOs say works Humans are the North Star for AI-native workplaces -- Gartner How IT leaders build a culture for what comes next Compliance costs risk widening the AI gap AI-driven layoffs add new demands on CIOs to prove value AI transformation: Early wins are not enough for CIOs Why CIOs can't let users wait on IT Memory shortage doesn't have to spell disaster for IT budgets Accelerate AI adoption: 3 reasons for adopting MCP How techno-nationalism is complicating IT resilience and supply chains for CIOs InformationWeek Podcast: Compliance crackdown on AI and BYOD Workday’s AI reset: Agents and the race to remake SaaS Why enterprise AI initiatives keep dying before production Metrics of meaning: What do we really measure in AI? Techno-nationalism is reshaping CIO infrastructure strategy Using AI to pick team leaders -- without crossing legal or ethical lines What Oracle's layoffs reveal about running IT with fewer people Chief AI Officer on course-correcting when AI moves too fast Large enterprises need high-performing networks to scale AI InformationWeek Podcast: When do smaller AI models make sense? The future belongs to AI-driven IT Ways AI supercharges risk awareness and data insights for CIOs How automation prepares you for agentic NetOps Should the CIO, CFO or CEO hold the kill switch on AI? The CIO's new mandate: Redesign work itself Ask the Experts: CIOs say they wouldn’t pull workloads back from the cloud How AI is Reshaping the Enterprise
Drive agentic AI outcomes with zero-based process redesign
Jan-Malte Prädel · 2026-06-23 · via informationweek

Agentic AI could create nearly $450 billion in value by 2028, helping organizations automate and orchestrate workflows if they reimagine their processes. 

Right now, only 2% of organizations have fully scaled agentic AI deployments, according to Capgemini Research Institute data. Part of the challenge many organizations face is the approach they take: They add AI agents to existing processes, rather than reimagine those processes entirely. By using a zero-based process redesign (ZBPR) strategy instead, organizations can leverage the full power of agentic AI to achieve operational efficiency at scale.

What is ZBPR, and why is it so important for agentic AI scalability? ZBPR requires remodeling processes from the ground up based on what agents can do, not the way things were done before. ZBPR avoids automating suboptimal workflows, and it makes the most of AI's agentic and orchestration capabilities. Designing an agent-native process gives organizations the opportunity to eliminate steps that don't create value or support compliance, and a chance to repurpose manual labor to better align the process align with strategic business goals. 

Related:Okta's Harish Peri on what it takes for CIOs to secure AI agents

Radical, not incremental, process redesign

Rather than deploying agentic AI incrementally within existing processes, ZBPR harnesses the contextual awareness, reasoning, planning and acting capabilities of agentic AI to radically transform processes. The result is workflows that optimize costs and efficiency, support risk management and compliance, and are more scalable and flexible than legacy processes without linear cost increases. 

For example, an employee onboarding process that used to require signing in to multiple platforms to handle account creation, payroll and equipment could be redesigned using a team of orchestrated agents. Those agents could handle all onboarding tasks for each new hire through a single point of contact. The agents and process could be adapted across different geographies and acquisitions for flexible scalability.

Other benefits of agent-native processes include the ability to run around the clock with minimal human oversight, shorter cycle times, more accurate data entry and real-time data visibility for compliance and insights. By eliminating rote, repetitive tasks, ZBPR can also increase employee availability for higher-value, more engaging work, such as dealing with edge cases and developing strategies based on agentic process insights. For example, with an expense-processing agent handling all employee expense reports below a certain threshold of value, the human manager can focus on higher-value reports and those with flagged anomalies. 

Related:Intuit's chief AI officer on the SaaSpocalypse and disciplined AI

The business impact of ZBPR

Organizations that have already implemented ZBPR for their agentic process transformation report higher AI ROI than organizations using less holistic automation strategies. The ROI improvement is due to not just greater efficiency. In some cases, the ZBPR plus AI approach allows organizations to automate workflows that previously couldn't be automated.

Consider an insurance contact center, where policyholders call or message with many different types of claims, varying levels of coverage and a patchwork of state laws governing their policies. An incremental agentic strategy would use a chatbot to handle the most basic inquiries, saving some time but not fundamentally transforming the experience for policyholders or service agents. A ZBPR redesign of the contact center workflow can fully leverage agentic capabilities.

For example, one general AI agent can triage and process most basic contacts from end to end. A team of more specialized agents can handle a large portion of the contacts that the main agent isn't trained to deal with. That leaves a smaller set of more complex or high-value issues for human agents to handle. By using ZBPR, the contact center can reduce costs, resolve issues faster for better customer experience and allow human agents to focus on the areas where their judgement and empathy matter the most.

Related:Time for an AI exit strategy: How CIOs are cutting AI waste

This example highlights a key trend. The most innovative adopters of agentic AI are shifting away from task-level automation to build multi-agent, end-to-end workflows that deliver more value than automating individual tasks. This shift is critical for organizations that want to future-proof for efficiency, agility and resilience. 

A practical roadmap for ZBPR and agentic AI 

Adopting a zero-based process redesign mindset requires a shift that starts at the top. Executives need to develop and share a clear vision of what's possible with agents and identify high-impact processes to pilot this approach. Next, zero-based process design workshops create agent-native workflows that achieve process outcomes more efficiently and support business goals for value creation. 

For each redesigned workflow, the organization must orchestrate multi-agent teams to handle all relevant processes. Humans must be in the loop as safeguards for edge cases and for compliance monitoring using real-time process data. As agentic pilots scale, organizations will need to reskill growing numbers of employees to manage AI agents or end-to-end agentic workflows. Reskilling should be part of a larger, ongoing cultural shift that positions agentic automation as a way to elevate employees' capabilities rather than replace them. Successful ZBPR transformations will depend heavily on compliance, governance and change management to ensure that employees and agents work together.

From AI-assisted to AI-orchestrated value

As organizations build out agentic workflows, change their culture and reskill their employees, they may benefit from creating a center of excellence for automation that tracks value at each step of the agentic transformation. A center of excellence can also help develop the next iteration of agentic AI value creation, whatever form that may take. For now, however, the key fact is that the future of processes and workflows isn't simply AI-assisted: It's AI-orchestrated and largely self-managing if organizations are bold enough to reimagine the way they work. 

About the Author

Jan-Malte Prädel

Capgemini Invent

Jan Malte Prädel is a senior director at Capgemini Invent in New York. Connecting insights from business process analysis and process data mining, he helps organizations uncover, analyze and solve business execution gaps.

Jan Malte has more than 20 years of experience in business process and IT consulting across North America and Europe, spanning diverse sectors and process domains. He specializes in helping organizations build programs, teams and momentum to tackle business challenges in a data-driven way that overcomes resistance toward successful transformation.