AI Transformation Consultant - Pre-Sales & Discovery

Location: Coimbatore, India

Client market: United States

Function: Business Development / AI Transformation Pre-Sales

Experience: 8 - 12 years

Working hours: Significant overlap with U.S. business hours

Role purpose:

Vserve is building an AI transformation practice that helps U.S. small and mid-sized businesses identify where AI, automation and workflow redesign can produce measurable business outcomes.

The AI Transformation Consultant will lead executive workshops, operational discovery and AI assessments for prospective and existing clients. The consultant's responsibility is not to sell AI tools indiscriminately. It is to understand how the client operates, identify high-value problems and convert those findings into a prioritized transformation roadmap and credible business case.

This is a senior, client-facing consulting and pre-sales position. The successful candidate will be equally comfortable interviewing a business owner, mapping an operational workflow, quantifying an opportunity and presenting recommendations to senior decision-makers.

Key responsibilities:

Executive workshops:

- Conduct structured AI opportunity workshops for U.S. SMB owners and leadership teams.

- Educate clients on practical applications of AI, automation, knowledge systems and process redesign.

- Help clients distinguish valuable business use cases from low-value experimentation.

- Facilitate discussions across business owners, functional leaders and operational users.

- Adapt workshop examples to different industries without relying on generic AI demonstrations.

Discovery and process diagnosis:

- Construct structured interviews with executives, department heads and process owners.

- Understand the client's business model, workflows, systems, constraints and growth objectives.

- Identify bottlenecks, repetitive activities, information gaps, decision delays and customer experience issues.

- Document current-state processes and define the business outcomes expected from improvement.

- Separate problems requiring process redesign from those that genuinely benefit from automation or AI.

AI opportunity assessment:

- Produce prioritized AI transformation assessments covering approximately three to seven opportunities.

- Score opportunities based on business value, implementation feasibility, risk, data readiness and time to impact.

- Develop current-state and future-state process maps with support from the AI Solutions Consultant.

- Estimate potential time savings, cost reduction, capacity creation, revenue impact and customer experience improvements.

- Create a phased roadmap that distinguishes quick wins from longer-term transformation initiatives.

Commercial conversion:

- Present assessment findings to client decision-makers in a persuasive, evidence-based format.

- Connect recommendations to the client's financial and strategic priorities.

- Position Vserve implementation services as the natural next step without compromising the independence of the assessment.

- Work with sales leadership to shape implementation offers, pricing and proposals.

- Support approximately five to eight completed assessments per month.

- Maintain disciplined follow-up until the opportunity is converted, deferred or closed.

Internal capability development:

- Build reusable discovery questionnaires, workshop modules, assessment frameworks and industry-specific use-case libraries.

- Capture recurring client problems and convert them into repeatable Vserve service offerings.

- Train business development and account management teams to recognize qualified AI transformation opportunities.

- Improve the assessment methodology based on implementation results and client feedback.

Expected deliverables:

For each qualified client engagement:

- Executive AI opportunity workshop

- Stakeholder interview notes and discovery transcript

- Current-state process analysis

- Prioritized AI and process-improvement opportunity matrix

- High-level future-state workflows

- Indicative ROI and business case

- Ninety-day action plan and longer-term roadmap

- Executive assessment presentation

- Implementation opportunity brief for the Vserve delivery team

Required experience and capabilities:

- Eight or more years in management consulting, business transformation, process excellence, enterprise pre-sales, digital transformation or a comparable client-facing role.

- Strong experience interviewing senior executives and operational stakeholders.

- Demonstrated ability to understand unfamiliar businesses quickly.

- Excellent process analysis, problem structuring and facilitation skills.

- Ability to translate operational problems into quantified business cases.

- Strong executive communication, presentation and consultative-selling skills.

- Working knowledge of generative AI, workflow automation, knowledge systems and modern SaaS platforms.

- Ability to use AI tools productively for research, analysis, synthesis and deliverable creation.

- Experience serving U.S. clients and communicating within a U.S. business context.

- Excellent spoken and written English.

Preferred background:

Candidates may come from:

- Management or technology consulting

- Digital transformation advisory

- Process excellence or business process management

- SaaS or automation pre-sales

- Business analysis with senior client-facing responsibility

- Intelligent automation or AI consulting

Experience in one or more SMB-intensive sectors - professional services, distribution, e-commerce, retail, healthcare administration, real estate, logistics or financial services - is advantageous.

Success measures:

- Five to eight high-quality assessments completed monthly by the pod

- Percentage of workshops progressing to formal assessments

- Percentage of assessments converting into paid implementation engagements

- Qualified implementation pipeline created

- Average projected and realized client value

- Assessment of turnaround time and client satisfaction

- Reusability and quality of the methodologies developed

- Accuracy of discovery findings compared with implementation-stage findings