XSparks, a global AI transformation company, has appointed Cosmo Mariano as Chief Client Outcomes Officer. A transformational leader with over 20 years of experience scaling and transforming technology businesses and customer operations, Mariano joins the company to bridge the gap between AI pilots and real business outcomes.
Mariano will lead clients’ AI business strategies across the XSparks portfolio. His counterpart, CTO Angad Singh Wadhwa, is leading the AI technology strategy. Together, their teams solve complex business problems using AI running in production and prove it with numbers that CEOs can present to the board.
This obligation covers the time and personnel that a company spends operating software rather than running a business. What Cosmo calls the “software tax.” Employees spend their days logging into and interacting with 10 systems. You work just to get the output you need for your job by finding data, copying it from one app to another, and manually updating records. Costs are measurable. Knowledge workers switch between applications nearly 1,200 times a day, spending just under four hours a week redirecting each switch (Harvard Business Review, 2022). The time loss is even more widespread across the workforce. According to research from Asana, the average knowledge worker spends about 60% of their day doing tasks related to their job, rather than the job itself.
Companies have invested heavily in AI. Corporate spending on generative AI more than tripled in one year, from $11.5 billion to $37 billion (Menlo Ventures, 2025). Yet, 56% of CEOs reported no economic benefit, and only 12% reported having both revenue and costs (PwC, 2026).
XSparks believes the deeper reason is structural. The first wave of enterprise AI was built to help people, not perform tasks. The co-pilot searches, summarizes, and makes suggestions while you manually interact with the software. The basic steps were never redesigned, so the work never left people. Individuals can now perform their tasks faster. The operating costs of the business remained the same and profits never changed.
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“People blame the AI. It wasn’t the AI that was the problem,” Mariano said. “Companies added it on top of their existing way of working, so procedures never changed and work never left employees. Tools brought individuals up to speed, but businesses ran the same way and P&Ls never changed. And pilots are not operating models, so pilots that showed promise stopped working before going live. To get there, workflows had to be redesigned and AI We need to stand up the infrastructure to run it, and let people operate it. That’s what we’re building. People are directing it and owning it.” ”
Rather than bolting AI into traditional operations as another tool, XSparks restructures companies to allow AI to run their operations. The company does this through one methodology: Think. build. Operations: Identify where AI moves your P&L, deliver your first working system in 4-6 weeks, and operate and improve it after launch. All engagements are guided by an AI Operating Model (AIOM). AIOM is the model that XSparks deploys across consulting, technology configuration, and managed operations. Its technology pillar is a seven-layer architecture that connects to the tools, data, and workflows businesses are already running, so AI can move across operations rather than stopping in a single pilot. XSparks reports its results in a quarterly figure called AI Return Multiple measured across cost, revenue, time, capacity, quality, and risk.
Mariano’s work spans three areas: business model design, product innovation, and restructuring: change management and training programs to develop employees. He helps CEOs redesign how their businesses make money around what is enabled by AI, shape new AI-native products that emerge from the restructuring, and build the enablement that turns plans on paper into teams that can execute them.
