AI Productivity and Work Expectations
Faisal Masud shares how AI is encouraging managers to set clearer expectations, empower employees with the right tools, and rethink how teams deliver results.
Faisal Masud
President of Worldwide Digital Services
Faisal Masud, President of Worldwide Digital Services at HP, joined the Everyday AI podcast to share his perspective on how AI is reshaping work. Drawing on his experience at HP, Staples, and Amazon — and as the CEO of a venture-backed startup — he explained why enterprises often lag in tech-driven productivity, how AI is reshaping job expectations, and why leaders must prioritize clear goals, secure tools, and AI use before expanding headcount. His insights offer a strategic blueprint for any leader looking to align employee expectations with the new realities of AI for work productivity.
Productivity gains with AI are greater in startups
According to a 2025 survey by GeekWire, nearly 90% of startup CEOs report AI is delivering moderate or major productivity gains. Meanwhile, 47% of C-suite execs at global companies say they’re developing GenAI tools too slowly, according to the 2025 AI in the Workplace report by McKinsey.
Large enterprises typically lag startups. Where you might see these massive gains in productivity in a startup — whether it's through Copilot and coding and customer service or something else where you use GenAI — those savings don't quite translate into enterprises at the same scale or size or percentages. So what might be 40% in a startup, when you translate that to an enterprise, it's probably much smaller.
Faisal Masud President of Worldwide Digital Services
With this in mind, meaningful AI gains will require enterprises to restructure workflows and retrain teams. Unlike startups, speed alone won’t drive impact. Scale demands intentional design.
AI tools let you raise the bar on expectations
With AI now embedded in day-to-day workflows, the baseline of performance has shifted. Leaders are expected to reassess what productivity looks like and revise job expectations as needed. According to scientific research published on the National Institute of Health (NIH) website, expectations set by managers ultimately determine an employee’s contributions to the workplace.
“You have to raise the bar on expectations. If your expectation was to get to X, now get to X plus, and see how the employee can catch up. And the task then is in the hands of the person doing the work to ensure that they can raise the bar themselves from where it is today.”
Faisal Masud President of Worldwide Digital Services @ HP
This approach shifts accountability back to the employee while recognizing that AI tools for work productivity are designed to boost efficiency. Organizations should not see AI as a crutch, but as a means to recalibrate what’s realistically possible.
Provide a secure environment for using AI tools
Security remains a critical barrier to enterprise AI adoption. Despite the benefits of generative AI, many organizations lack clear guardrails. According to the 2025 Cybersecurity Attitudes and Behaviors Report by CybSafe and the National Cybersecurity Alliance, 38% of people share sensitive work information with AI without their employer’s knowledge. This reveals a serious vulnerability that cannot be ignored.
“AI is really good at the thought starting process in which you can use these tools. The problem that employers have is the data from their company that's being exposed to these platforms. So you should build versions of ChatGPT internally that are super powerful and don't require you to go outside your enterprise. A lot of dependency is still on the cloud-based versions of LLMs.”
Faisal Masud President of Worldwide Digital Services @ HP
To maintain trust and protect intellectual property, companies must enable secure, internal access to large language models. This ensures that employee expectations with AI are met without compromising enterprise data integrity.
Set clear expectations and don't micromanage
Many productivity issues stem from ambiguity rather than underperformance. A 2024 Gallup poll found that only 45% of U.S. employees know what’s expected of them at work (down from 61% in 2015), reflecting a growing communication gap between leadership and staff. Clear expectations combined with autonomy can dramatically improve work productivity.
“If you define the expectation to deliver X by Y date and that is happening, why would I be mad at anybody about using AI? And if I expected more, then I should be mad at myself. Because the employees are doing exactly what they were asked to do. How they get to that end state is up to them. Obviously, those using AI are going to excel because they'll have an accelerated pace of doing what they're doing, and kudos to them. But to the earlier point, you have to raise the bar.”
Faisal Masud President of Worldwide Digital Services @ HP
Combining defined goals with autonomy and the right AI support gives employees the space to work smarter. This also aligns with evolving employee expectations with AI in that people want clarity, tools, and trust.
AI tools can help prevent overhiring
In the face of skill gaps, many organizations instinctively turn to hiring. But this can lead to bloated teams and reduced agility. Instead, executives and managers are much more likely to cite skill building, rather than hiring, as the most effective way to close skill gaps according to a McKinsey Global Survey.
“Hiring more people to do the work is usually not the answer. Having a very large team introduces a ton of complexity in just getting the work done. So many handshakes along the way, so much bureaucracy. The employees are not happy. The employer is probably going to struggle too. So the less is more approach is quite valuable here. Do more with less. That doesn't mean put more work on the employees, but enable them through a toolkit instead of hiring armies of people.”
Faisal Masud President of Worldwide Digital Services @ HP
AI for work productivity can be a lever for leaner, more effective teams. Instead of scaling through headcount, organizations should invest in smarter systems and empower their existing workforce.
In conclusion, AI is redefining how work gets done and how organizations should think about productivity, talent, and scale. Startups are seeing early wins by acting fast, but enterprises can also benefit by updating their approach to job expectations and building secure, internal AI environments. The key lies in clear communication, strategic use of AI tools for work productivity, and resisting the impulse to overhire. As Masud points out, enabling teams with the right technology leads to stronger outcomes and ultimately more agile and resilient organizations.
