Richie Adetimehin has built a career helping enterprises bridge the divide between technology and business value by making the most out of the cloud platform ServiceNow. The real story is not about technology at all. For him, measurable ROI emerges only when organizations treat ServiceNow AI as a strategic lever rather than a catalog of […] The post Richie Adetimehin: How to Align ServiceNow AI With Strategic Business Outcomes appeared first on TechBullion.Richie Adetimehin has built a career helping enterprises bridge the divide between technology and business value by making the most out of the cloud platform ServiceNow. The real story is not about technology at all. For him, measurable ROI emerges only when organizations treat ServiceNow AI as a strategic lever rather than a catalog of […] The post Richie Adetimehin: How to Align ServiceNow AI With Strategic Business Outcomes appeared first on TechBullion.

Richie Adetimehin: How to Align ServiceNow AI With Strategic Business Outcomes

2025/12/10 18:36

Richie Adetimehin has built a career helping enterprises bridge the divide between technology and business value by making the most out of the cloud platform ServiceNow. The real story is not about technology at all. For him, measurable ROI emerges only when organizations treat ServiceNow AI as a strategic lever rather than a catalog of features. “When you anchor AI to outcomes that matter, the platform stops being another tool and starts becoming a catalyst for enterprise-wide performance,” says Adetimehin.

The platform becomes transformative when leaders elevate fulfiller and requester experiences, reinforce governance and tie every AI capability back to a clear business outcome. That alignment is what turns ServiceNow into the engine of an enterprise rather than another system competing for attention.

Bridging the Divide Between Technology and Business Value

Many ServiceNow programs launch successfully, yet six months later leaders find themselves confronting inconsistent processes, low adoption, confusing dashboards and an unclear return on investment.

According to Richie Adetimehin, the turning point lies in linking AI capabilities to strategic intent rather than treating them as isolated features. “My key drive comes from witnessing firsthand how solutions with ServiceNow like Now Assist transform organizations from IT-driven operations to true business value engines,” he explains. His experience spans ITSM, Enterprise Architecture, CSM and CMDB transformations, giving him a front-row seat to how AI accelerates outcomes when implemented with precision and clarity.

Why Companies Struggle to Connect AI to ROI

Despite growing interest in ServiceNow AI capabilities, most organizations find it difficult to quantify impact. Adetimehin attributes this to an overemphasis on tools rather than outcomes. “Many companies struggle to link ServiceNow AI capabilities to return on investment because alignment requires bridging technology with business strategy and operations,” he says.

Leaders tend to push ahead without defining KPIs and mapping AI use cases to platform capabilities and process improvements. Deloitte reports that 42% of AI projects stall because organizations fail to articulate measurable outcomes early in the process while research from Gartner found that fewer than half of AI initiatives make it from pilot to production due to unclear objectives.

“Organizations get stuck in the technology adoption phase. They focus more on features than outcomes, and that leads to fragmented efforts,” Adetimehin adds.

The Three Steps That Drive Measurable ROI

Adetimehin’s work has delivered outcomes such as 20 percent reductions in MTTR, improved workflow intelligence and major increases in platform adoption. When asked how companies can replicate this success, he shares three practical steps.

1. Set Outcome-Based KPIs: Before any AI rollout, leaders must determine which business outcomes matter most. “Map specific Now Assist use cases to measurable targets to reduce MTTR, deflect cases, increase time to value, increase first-contact resolution or boost data quality scores” he says.

2. Empower Fulfillers first before Requesters: Adetimehin emphasizes improving the live agent experience as the fastest path to value impact. Agents often spend nearly 40 percent of their time documenting incidents. “With Now Assist, agents can save 10 to 15 minutes per ticket,” he says. That leads to faster resolution, reduced backlog and less burnout.”

3. Drive Adoption and Continuous Feedback: AI initiatives cannot succeed without ongoing reinforcement. “Invest in training, change management and feedback mechanisms that capture real fulfiller and requester experience,” he advises.

The Road Ahead: AI as a Performance Catalyst

The rapid evolution of AI in service management is reshaping enterprise performance. ServiceNow’s own data shows reductions in manual work, faster incident resolution and improved customer satisfaction. The next frontier lies in predictive and preventative workflows that mitigate issues before they impact operations where ServiceNow Agentic Workflow redefines automation in business operations.

“In the coming years, those leveraging ServiceNow AI capabilities will set new benchmarks for agility, risk management and customer centricity,” he says.

Connect with Richie Adetimehin on LinkedIn for more insights and guidance on maximizing ServiceNow investments.

Comments
Disclaimer: The articles reposted on this site are sourced from public platforms and are provided for informational purposes only. They do not necessarily reflect the views of MEXC. All rights remain with the original authors. If you believe any content infringes on third-party rights, please contact service@support.mexc.com for removal. MEXC makes no guarantees regarding the accuracy, completeness, or timeliness of the content and is not responsible for any actions taken based on the information provided. The content does not constitute financial, legal, or other professional advice, nor should it be considered a recommendation or endorsement by MEXC.

You May Also Like

What Every Platform Eventually Learns About Handling User Payments Across Borders

What Every Platform Eventually Learns About Handling User Payments Across Borders

There is a moment almost every global platform hits. It rarely shows up in dashboards or board meetings. It reveals itself quietly, one payout del
Share
Medium2025/12/10 21:54
Kalshi debuts ecosystem hub with Solana and Base

Kalshi debuts ecosystem hub with Solana and Base

The post Kalshi debuts ecosystem hub with Solana and Base appeared on BitcoinEthereumNews.com. Kalshi, the US-regulated prediction market exchange, rolled out a new program on Wednesday called KalshiEco Hub. The initiative, developed in partnership with Solana and Coinbase-backed Base, is designed to attract builders, traders, and content creators to a growing ecosystem around prediction markets. By combining its regulatory footing with crypto-native infrastructure, Kalshi said it is aiming to become a bridge between traditional finance and onchain innovation. The hub offers grants, technical assistance, and marketing support to selected projects. Kalshi also announced that it will support native deposits of Solana’s SOL token and USDC stablecoin, making it easier for users already active in crypto to participate directly. Early collaborators include Kalshinomics, a dashboard for market analytics, and Verso, which is building professional-grade tools for market discovery and execution. Other partners, such as Caddy, are exploring ways to expand retail-facing trading experiences. Kalshi’s move to embrace blockchain partnerships comes at a time when prediction markets are drawing fresh attention for their ability to capture sentiment around elections, economic policy, and cultural events. Competitor Polymarket recently acquired QCEX — a derivatives exchange with a CFTC license — to pave its way back into US operations under regulatory compliance. At the same time, platforms like PredictIt continue to push for a clearer regulatory footing. The legal terrain remains complex, with some states issuing cease-and-desist orders over whether these event contracts count as gambling, not finance. This is a developing story. This article was generated with the assistance of AI and reviewed by editor Jeffrey Albus before publication. Get the news in your inbox. Explore Blockworks newsletters: Source: https://blockworks.co/news/kalshi-ecosystem-hub-solana-base
Share
BitcoinEthereumNews2025/09/18 04:40
U.S. AI leaders form foundation to compete with China

U.S. AI leaders form foundation to compete with China

The post U.S. AI leaders form foundation to compete with China appeared on BitcoinEthereumNews.com. A group of leading U.S. artificial intelligence firms has formed a new foundation to establish open standards for “agentic” AI. The founding members, OpenAI, Anthropic, and Block, have pooled their proprietary agent- and AI-related technologies into a new open-source project called the Agentic AI Foundation (AAIF), under the auspices of the Linux Foundation. This development follows tensions in the global race for dominance in artificial intelligence, leading U.S. AI firms and policymakers to unite around a new push to preserve American primacy. Open standards like MCP drive innovation and cross-platform collaboration Cloudflare CTO Dane Knecht noted that open standards and protocols, such as MCP, are critical for establishing an evolving developer ecosystem for building agents. He added, “They ensure anyone can build agents across platforms without the fear of vendor lock-in.” American companies face a dilemma because they are seeking continuous income from closed APIs, even as they are falling behind in fundamental AI development, risking long-term irrelevance to China. And that means American companies must standardize their approach for MCP and agentic AI, allowing them to focus on building better models rather than being locked into an ecosystem. The foundation establishes both a practical partnership and a milestone for community open-sourcing, with adversaries uniting around a single goal of standardization rather than fragmentation. It also makes open-source development easier and more accessible for users worldwide, including those in China. Anthropic donated its Model Context Protocol (MCP), a library that allows AIs to utilize tools creatively outside API calls, to the Linux Foundation. Since its introduction a year ago, MCP has gained traction, with over 10,000 active servers, best-in-class support from platforms including ChatGPT, Gemini, Microsoft Copilot, and VS Code, as well as 97 million monthly SDK downloads. “Open-source software is key to creating a world with secure and innovative AI tools for…
Share
BitcoinEthereumNews2025/12/10 22:10