Manmohan Gosada is Co-founder and Chief Technology Officer at ExpandIQ, where he helps organisations turn AI into working systems that improve efficiency, reduce wasted effort and create measurable business value.
He leads the technical side of ExpandIQ's work across AI engineering, solution design, implementation, governance, integration and rollout. His focus is not on building technology for its own sake. It is on making sure AI solves a real business problem, fits the way the organisation works, and holds up in day-to-day use.
At ExpandIQ, Manmohan works with leadership teams and operational stakeholders to move from AI interest to practical delivery. That includes helping clients choose the right tools, connect AI to existing systems and data, build governed solutions, and create the technical foundations needed for adoption at scale.
About Manmohan
Manmohan brings a strong mix of data science, analytics, pricing, product and technical delivery experience across legal, banking, consulting and commercial environments.
His background is grounded in solving business problems through data, machine learning and applied AI. Over time, that work evolved from analytics and modelling into broader product, platform and AI implementation work, giving him a practical view of what it takes to build solutions that are both technically sound and commercially useful.
That perspective sits at the heart of ExpandIQ's approach. Manmohan does not see implementation as simply shipping a tool. He sees it as the work of designing and building something that improves a process, supports better decisions, and can be governed safely as the business scales its use of AI.
What Manmohan writes about
Manmohan writes about the technical and operational side of AI adoption, including:
- AI implementation and engineering
- governance and secure AI rollout
- workflow automation
- tool selection and build vs buy decisions
- connecting AI to business systems and knowledge
- data foundations for AI
- proof-of-value delivery
- AI operating models
- forecasting, pricing and analytics applications
- practical ways to reduce manual work with AI
His articles are shaped by a simple principle: useful AI should improve efficiency, save cost, support better output and contribute to the bottom line.
Experience and background
Co-founder & Chief Technology Officer, ExpandIQ
Dec 2025 – PresentAs Co-founder and CTO of ExpandIQ, Manmohan leads technical architecture, engineering and implementation across the business.
His work spans:
- AI solution design and build
- technical delivery across client environments
- governed AI implementation
- tool and platform evaluation
- connecting AI to business systems, documents and knowledge
- workflow automation and process improvement
- building technical foundations that support secure adoption
- supporting TeamHiiv as part of ExpandIQ's broader AI capability
A key part of Manmohan's role is helping clients move beyond basic experimentation. He focuses on building practical solutions that work inside real business processes and are supported by the right controls, governance and technical fit.
Head of Pricing and Analytics, Scalene
Feb 2025 – Nov 2025In this role, Manmohan led work across pricing and analytics, bringing together commercial logic, modelling and technical problem-solving.
Head of Product and Analytics, Hakea Consulting
Jun 2023 – Nov 2025At Hakea Consulting, Manmohan worked across product and analytics leadership, helping shape solutions that linked data, decision-making and applied technology.
Senior Data Scientist, Maurice Blackburn Lawyers
Jan 2022 – Jun 2023At Maurice Blackburn, Manmohan worked on applied data science in a complex legal services environment. This period is also significant because it is where he worked closely with Jonas before the two later co-founded ExpandIQ together.
That matters. They did not come together as strangers. They had already worked in a live operating environment, seen how each other think, and built trust through delivery.
Consultant, National Australia Bank
May 2019 – Jan 2022Manmohan's consulting experience at NAB added depth across enterprise environments, stakeholder needs and practical application of analytics and data-led solutions.
Data Scientist, Lion
Sep 2018 – Apr 2019At Lion, Manmohan worked across:
- price and promotion optimisation
- demand planning using machine learning
- price elasticity modelling
- consumer segmentation and behaviour analysis
- web scraping for competitor pricing
- data warehousing and data management
- visualisation using tools including R Shiny, Power BI and Plotly
This mix of commercial modelling and technical execution remains relevant to the way he approaches AI today: grounded, useful and connected to business outcomes.
Manmohan's approach to AI
Manmohan's view of AI is practical and clear-eyed.
He believes organisations struggle with AI when they focus too heavily on tools and not enough on process, context, governance and fit. In his view, AI only becomes useful when a business has the right foundations in place and a clear understanding of what the technology should and should not be used for.
His approach is built around a few core ideas:
- strategy should point to a business outcome worth having
- the process often needs fixing before the tool can help
- AI needs the right context and data to produce useful outputs
- governance matters from the start, not later
- speed and control can work together if the right tools and checks are in place
- practical value comes from efficiency gained, cost saved, revenue supported and output quality improved
That makes him a strong technical voice for organisations trying to sort through AI noise and build something that actually works.
What Manmohan helps clients with
Across ExpandIQ engagements, Manmohan commonly helps clients with:
- assessing which AI use cases are worth pursuing first
- deciding between Copilot, ChatGPT, Gemini or a custom solution
- designing AI systems that fit existing business workflows
- building secure, governed AI solutions
- reducing tool sprawl through better platform and governance decisions
- connecting AI to internal documents, systems and knowledge bases
- improving document-heavy workflows such as proposals, reports, agreements and presentations
- creating proof-of-value solutions tied to measurable outcomes
- supporting AI rollout with the right technical and operational design
Practical areas of expertise
Manmohan has particular depth in:
A grounded view of implementation
One of Manmohan's strongest points of view is that building technology is only half the job.
A solution still needs to fit the business, improve the process and be trusted by the people using it. That is why his work sits across more than engineering alone. He looks at where the bottlenecks are, what the workflow actually requires, how the technology should connect into current systems, and what controls need to exist for the business to use AI safely at scale.
This is also where ExpandIQ's model stands apart from firms that stop at advice or firms that only deliver technical builds. Manmohan's role helps bridge that gap by turning strategy into usable implementation.
What readers can expect from Manmohan's articles
Articles by Manmohan are suited to leaders and teams who want to understand how AI gets implemented properly, not just discussed at a high level.
Readers can expect writing that is:
- practical
- technically credible
- commercially aware
- grounded in workflow reality
- clear on trade-offs
- focused on governed, useful outcomes
His articles will often cover how businesses can reduce manual work, improve output consistency, connect AI to the right context and data, and avoid the governance issues that come with fragmented tool use.
Connect with Manmohan
To follow Manmohan's work, insights and updates: