The big firms built their own AI impact tech.
Win more AI transformation work with an enterprise-grade capability your team can use across clients, without building the tech yourself.
Every AI strategy needs a workforce answer. Almost nobody can build one.
Boards have stopped asking whether there's an AI strategy and started asking what it returns. Your client's chief executive has a platform roadmap and a pile of pilots. Neither one says what changes in the business, what it saves, or who it affects.
The data gap
Readiness scores and benchmarks cannot tell a CFO which opportunity to fund first. That answer sits one level down, in the tasks.
The time gap
Doing it by hand means interviews and a time and motion study. Slow, expensive, and it rattles the workforce before you conclude anything.
The credibility gap
Without evidence underneath it, workforce advice is a point of view. It loses to the business case next to it on the agenda.
One upload. Every future your client wants to test.
Every role is broken down into tasks, each assessed for its potential to change with AI. Pick a role, choose an AI adoption scenario and select a timeframe. See how the results change and what’s driving them.
PICK A ROLE
Choose an AI adoption scenario
Choose a timeframe
Industry pace
People Business Partner · 2 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
33%
Human initiated, AI responds
56%
AI led, human oversight
11%
Advise leaders on performance and conduct matters
Advice on sensitive performance and conduct issues requires contextual judgement and trust that AI cannot replicate at this stage.
Coach leaders on difficult conversations
Coaching leaders through difficult, emotionally-charged conversations relies on relational trust and lived judgement that AI cannot provide.
Partner on workforce planning and organisational design
AI tools support scenario modelling and workforce data analysis but strategic design decisions remain firmly with the business partner and leaders.
Manage restructures and role changes
AI supports documentation and impact analysis for restructures, but process management and change leadership remain human-driven.
Drive engagement and succession planning
AI-generated engagement and talent analytics inform planning discussions, while strategy and prioritisation remain human-led.
Investigate employee conduct and grievance matters
AI helps organise evidence and case timelines, but investigation judgement and interviews remain human-led.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
Industry pace
People Business Partner · 3 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
28%
Human initiated, AI responds
38%
AI led, human oversight
34%
Advise leaders on performance and conduct matters
AI may surface relevant policy or precedent information, but the advisory relationship and decision remain human-led.
Coach leaders on difficult conversations
AI simulation tools may emerge for practice scenarios but genuine coaching remains a human-only capability.
Partner on workforce planning and organisational design
Enterprise workforce planning platforms provide richer predictive modelling, increasing AI input to design options while decisions stay human-led.
Manage restructures and role changes
Vendor HR platforms increasingly automate role mapping and cost modelling, reducing manual analysis time.
Drive engagement and succession planning
Predictive analytics on flight risk and readiness become more embedded, increasing AI's role in shaping the conversation.
Investigate employee conduct and grievance matters
Case management platforms with AI-assisted analysis improve evidence synthesis, but findings and recommendations stay human-determined.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
Industry pace
People Business Partner · 5 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
4%
Human initiated, AI responds
47%
AI led, human oversight
38%
Fully automated
11%
Advise leaders on performance and conduct matters
AI assists by drafting talking points and summarising precedent cases, though the nuanced advice itself stays human-delivered.
Partner on workforce planning and organisational design
AI-generated organisational design scenarios become standard inputs, but judgement on structure, culture fit and strategy remains a human capability.
Coach leaders on difficult conversations
AI-powered conversation simulators help leaders rehearse scenarios, supplementing but not replacing human coaching.
Drive engagement and succession planning
AI provides sophisticated succession modelling and engagement forecasting, but final judgement calls on talent and culture remain human.
Manage restructures and role changes
Workflow platforms orchestrate much of the restructure process end-to-end, with the People Business Partner overseeing compliance and sensitive decisions.
Investigate employee conduct and grievance matters
AI assists with pattern detection across similar cases and drafts investigation summaries, with humans retaining decision-making authority given the sensitivity.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
Proactive investment
People Business Partner · 2 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
28%
Human initiated, AI responds
44%
AI led, human oversight
28%
Advise leaders on performance and conduct matters
Even with proactive AI investment, sensitive performance and conduct advice remains human-only due to the trust and contextual judgement required.
Coach leaders on difficult conversations
Coaching remains a human-only activity even under proactive investment, as trust-based development cannot be delegated to AI at this stage.
Partner on workforce planning and organisational design
Proactively deployed workforce planning tools generate scenario models and predictive insights that the business partner uses to shape design decisions, accountable for the final call.
Manage restructures and role changes
Pilot automation of role mapping, cost modelling and documentation accelerates restructure preparation, with the business partner directing the process.
Drive engagement and succession planning
Proactively adopted engagement and talent analytics tools generate richer insights that accelerate planning discussions led by the business partner.
Investigate employee conduct and grievance matters
AI-assisted case analysis tools are piloted to organise evidence and identify patterns, speeding up investigations led by the business partner.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
Proactive investment
People Business Partner · 3 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
4%
Human initiated, AI responds
47%
AI led, human oversight
38%
Fully automated
11%
Advise leaders on performance and conduct matters
Specialist HR AI tools begin drafting guidance and precedent summaries to support the business partner's advisory conversations.
Partner on workforce planning and organisational design
Specialist workforce planning AI vendors are scaled enterprise-wide, producing increasingly sophisticated design options that the business partner curates.
Coach leaders on difficult conversations
AI-powered simulation and rehearsal tools are piloted and scaled to help leaders practice difficult conversations, supplementing human coaching.
Drive engagement and succession planning
Predictive succession and engagement models are scaled across the bank, increasingly shaping strategy while final decisions remain human.
Manage restructures and role changes
Scaled enterprise workflow tools autonomously manage much of the restructure process, with the business partner overseeing sensitive decisions and compliance.
Investigate employee conduct and grievance matters
Scaled AI case management autonomously synthesises evidence and drafts findings summaries, with humans retaining decision authority given sensitivity.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
Proactive investment
People Business Partner · 5 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human initiated, AI responds
28%
AI led, human oversight
56%
Fully automated
16%
Advise leaders on performance and conduct matters
AI-assisted case guidance becomes embedded in the advisory workflow, though the relationship-based delivery of advice stays human-led.
Coach leaders on difficult conversations
AI conversation simulators become a standard preparation tool, but the coaching relationship and judgement remain human-delivered.
Partner on workforce planning and organisational design
Mature AI platforms autonomously generate and stress-test organisational design options, with the business partner providing oversight and final strategic decisions.
Manage restructures and role changes
Restructure orchestration is largely automated end-to-end through mature platforms, with human oversight concentrated on high-risk or contentious cases.
Drive engagement and succession planning
AI autonomously identifies engagement risks and succession gaps at scale, with the business partner overseeing strategic prioritisation and stakeholder alignment.
Investigate employee conduct and grievance matters
AI handles substantial investigative groundwork and pattern detection across cases, with human oversight essential for final determinations and natural justice.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
AI-first transformation
People Business Partner · 2 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
8%
Human initiated, AI responds
50%
AI led, human oversight
42%
Advise leaders on performance and conduct matters
AI generates precedent-based guidance and drafts advisory content at scale, though the trusted advisory relationship with leaders remains human-directed.
Partner on workforce planning and organisational design
AI-first workforce planning tools generate comprehensive design scenarios and predictive models, with the business partner directing priorities and applying judgement.
Coach leaders on difficult conversations
AI-powered simulation tools are deployed at scale to help leaders rehearse difficult conversations, though genuine coaching remains human-led.
Drive engagement and succession planning
AI engagement and succession platforms generate deep predictive insights at scale, with the business partner directing strategic priorities.
Investigate employee conduct and grievance matters
AI autonomously organises evidence, timelines and precedent analysis for investigations, though findings and determinations remain human-directed.
Manage restructures and role changes
AI agents autonomously manage role mapping, cost modelling and process sequencing for restructures, with the business partner overseeing compliance and sensitive decisions.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
AI-first transformation
People Business Partner · 3 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
4%
Human initiated, AI responds
24%
AI led, human oversight
56%
Fully automated
16%
Advise leaders on performance and conduct matters
AI increasingly proposes recommended courses of action for performance and conduct matters, with the business partner validating and personalising delivery.
Coach leaders on difficult conversations
AI coaching assistants provide tailored preparation content and real-time conversational guidance, augmenting but not replacing the human coach.
Partner on workforce planning and organisational design
Enterprise AI platforms autonomously generate and refine organisational design options across the bank, with the business partner overseeing strategic alignment.
Manage restructures and role changes
Restructure workflows run largely autonomously across enterprise platforms, with humans retained principally for legally required consultation oversight.
Drive engagement and succession planning
AI autonomously models succession scenarios and engagement interventions across the division, with human oversight on strategic prioritisation and stakeholder engagement.
Investigate employee conduct and grievance matters
AI conducts substantial evidence synthesis and drafts investigation findings, with humans retaining decision authority given natural justice requirements.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
AI-first transformation
People Business Partner · 5 years
They automate everything AI can handle and rebuild teams around what is left.
Human initiated, AI responds
16%
AI led, human oversight
62%
Fully automated
22%
Coach leaders on difficult conversations
Even under AI-first transformation, coaching retains a human core because leadership development depends on trust and lived experience that AI cannot fully.
Advise leaders on performance and conduct matters
AI autonomously drafts tailored advice and recommended actions based on case history and policy, with the business partner providing final human oversight.
Partner on workforce planning and organisational design
Workforce planning is substantially AI-driven end-to-end, with human involvement concentrated on validating strategic fit and culture implications where judgement matters.
Manage restructures and role changes
End-to-end restructure orchestration is AI-led, with human involvement reserved for legal sign-off and highly sensitive individual cases.
Drive engagement and succession planning
Engagement and succession strategy is largely AI-generated and continuously updated, with humans retained to validate cultural nuance and make final talent.
Investigate employee conduct and grievance matters
Investigations are heavily AI-supported end-to-end, with human oversight preserved specifically where procedural fairness and legal accountability require.
Displaying the top six biggest tasks, about 50% of the role. 16 in total.
Industry pace
Technology Finance Analyst · 2 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
10%
Human initiated, AI responds
90%
Prepare monthly technology budget and forecast
Copilot-enabled templates and cloud finance tools draft baseline budget and forecast figures from actuals, with the analyst refining assumptions and finalising the numbers.
Build showback cost reporting
Cloud cost and BI platforms generate draft showback views that the analyst configures, validates and distributes.
Conduct budget variance analysis
BI tools and Copilot flag variances and draft commentary, but the analyst validates root causes and business context.
Forecast cloud consumption costs
Native cloud cost management tools produce baseline consumption forecasts that the analyst refines using business context.
Assess project cost capitalisation
AI tools assist in applying accounting standards to project data, but capitalisation judgement remains with the analyst given compliance sensitivity.
Model cost impact of sourcing decisions
AI-assisted scenario modelling accelerates analysis of sourcing options, but the analyst frames assumptions and interprets commercial implications.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
Industry pace
Technology Finance Analyst · 3 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
8%
Human initiated, AI responds
33%
AI led, human oversight
59%
Assess project cost capitalisation
AI improves consistency of documentation review and standard application, but final capitalisation assessment remains a human decision.
Model cost impact of sourcing decisions
AI tools generate more sophisticated cost scenarios, though sourcing strategy decisions remain human-led given vendor relationship complexity.
Prepare monthly technology budget and forecast
AI systems auto-generate first-pass budgets and forecasts by pulling directly from core banking and cloud cost platforms; the analyst reviews and adjusts figures.
Build showback cost reporting
Showback reporting increasingly runs on automated pipelines with pre-built allocation logic; analyst intervention shifts to exception handling and stakeholder queries.
Conduct budget variance analysis
Automated variance detection and narrative generation become embedded in standard reporting, with the analyst focused on reviewing exceptions.
Forecast cloud consumption costs
Cloud platform AI forecasting matures, generating near-continuous consumption projections reviewed periodically by the analyst.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
Industry pace
Technology Finance Analyst · 5 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
3%
Human initiated, AI responds
10%
AI led, human oversight
61%
Fully automated
26%
Prepare monthly technology budget and forecast
Continuous, largely autonomous re-forecasting becomes standard across enterprise finance platforms, with the analyst retaining oversight for material judgements.
Conduct budget variance analysis
Continuous automated variance monitoring with AI-generated commentary is routine; human input is reserved for material or ambiguous exceptions.
Assess project cost capitalisation
AI systems pre-assess capitalisation eligibility against accounting standards, with the analyst validating and overseeing higher-risk cases.
Model cost impact of sourcing decisions
AI-driven scenario modelling handles most quantitative analysis autonomously, with human oversight retained for strategic sourcing decisions.
Build showback cost reporting
Integrated cloud cost management and BI platforms auto-generate and distribute showback reports with minimal human involvement.
Forecast cloud consumption costs
Cloud vendor AI-driven forecasting tools deliver highly accurate, continuously updated consumption forecasts with limited need for manual modelling.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
Proactive investment
Technology Finance Analyst · 2 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
8%
Human initiated, AI responds
33%
AI led, human oversight
59%
Assess project cost capitalisation
AI tools assess project data against capitalisation rules and flag likely treatment, but the analyst retains judgement given compliance implications.
Model cost impact of sourcing decisions
AI scenario modelling tools rapidly generate cost impact analyses for sourcing options, with the analyst shaping assumptions and interpreting commercial context.
Prepare monthly technology budget and forecast
Proactive AI investment enables auto-generation of budgets and forecasts directly from integrated banking and cloud data platforms, with the analyst review.
Build showback cost reporting
Enterprise AI and cloud cost platforms generate showback reports with configuration and validation support from the analyst.
Conduct budget variance analysis
AI variance detection and commentary generation are scaled enterprise-wide early, with the analyst reviewing flagged exceptions rather than performing manual analysis.
Forecast cloud consumption costs
Specialist cloud cost AI tools deliver detailed consumption forecasts, with the analyst validating outputs against business plans.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
Proactive investment
Technology Finance Analyst · 3 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
3%
Human initiated, AI responds
10%
AI led, human oversight
61%
Fully automated
26%
Prepare monthly technology budget and forecast
Rolling, continuously updated forecasts become the norm across the bank's finance platforms; the analyst intervenes mainly for strategic adjustments and significant variances.
Conduct budget variance analysis
Automated variance monitoring becomes near real-time and highly reliable, with human involvement limited to material or ambiguous cases.
Assess project cost capitalisation
AI systems apply accounting standards more autonomously to capitalisation assessments, with the analyst validating higher-risk or ambiguous cases.
Model cost impact of sourcing decisions
AI autonomously runs multi-scenario cost modelling for sourcing decisions, with human oversight applied to final recommendations.
Build showback cost reporting
Showback reporting pipelines operate autonomously with embedded allocation logic, requiring minimal human configuration.
Forecast cloud consumption costs
Cloud vendor and enterprise AI tools produce highly accurate, continuously updated forecasts requiring negligible manual input.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
Proactive investment
Technology Finance Analyst · 5 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
3%
Human initiated, AI responds
10%
AI led, human oversight
43%
Fully automated
44%
Prepare monthly technology budget and forecast
Forecasting is highly autonomous and enterprise-wide, but human oversight is retained for strategic allocation decisions and governance requirements.
Assess project cost capitalisation
Capitalisation assessment is largely AI-driven using standardised rules engines, with human oversight preserved for judgement-intensive and high-value projects.
Model cost impact of sourcing decisions
Sourcing cost modelling is highly automated and integrated with vendor and market data, though strategic sourcing decisions retain human oversight.
Build showback cost reporting
Showback reporting is fully integrated into automated finance and cloud platforms, with human involvement only for occasional structural changes.
Conduct budget variance analysis
Routine variance analysis and narrative generation run autonomously across finance systems, with exception escalation handled through automated thresholds.
Forecast cloud consumption costs
Cloud consumption forecasting is fully autonomous, integrated across procurement, engineering and finance systems.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
AI-first transformation
Technology Finance Analyst · 2 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
8%
Human initiated, AI responds
5%
AI led, human oversight
61%
Fully automated
26%
Prepare monthly technology budget and forecast
AI-first finance platforms autonomously generate and continuously adjust budgets and forecasts from live data, with a named human retaining governance sign-off.
Conduct budget variance analysis
AI agents autonomously detect variances and generate root-cause commentary, with human review focused only on material exceptions.
Assess project cost capitalisation
AI applies capitalisation rules to project data autonomously, but accounting standards require human validation of judgement-based assessments.
Model cost impact of sourcing decisions
AI agents autonomously generate multi-scenario cost impact models for sourcing options, with humans providing strategic framing and final judgement.
Build showback cost reporting
Showback reporting is a non-judgemental, rules-based process that AI-first platforms automate end-to-end early in the transformation.
Forecast cloud consumption costs
Specialist cloud AI agents deliver continuous, highly accurate consumption forecasts without need for manual modelling in an AI-first environment.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
AI-first transformation
Technology Finance Analyst · 3 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
3%
Human initiated, AI responds
10%
AI led, human oversight
43%
Fully automated
44%
Prepare monthly technology budget and forecast
Budgeting becomes an almost fully autonomous, continuously updated process; human involvement is limited to accountable sign-off under financial governance.
Assess project cost capitalisation
AI-driven capitalisation assessment matures significantly, but professional accounting judgement retained by humans is required under regulatory and audit.
Model cost impact of sourcing decisions
Sourcing cost modelling becomes highly autonomous and integrated with vendor and market intelligence, though strategic sourcing decisions retain human oversight.
Build showback cost reporting
Showback pipelines operate fully autonomously across all cost centres with no manual configuration required.
Conduct budget variance analysis
Variance analysis and commentary generation run end-to-end without human involvement, as AI-first workflows mature and confidence in automated outputs grows.
Forecast cloud consumption costs
Cloud consumption forecasting operates fully autonomously, integrated across procurement, engineering and finance systems.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
AI-first transformation
Technology Finance Analyst · 5 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
3%
Human initiated, AI responds
10%
AI led, human oversight
43%
Fully automated
44%
Prepare monthly technology budget and forecast
Despite near-complete automation of budget generation, banking governance and accountability regimes require a designated human to approve and own financial outcomes.
Assess project cost capitalisation
Even under maximum practical automation, capitalisation determinations affecting financial statements require accountable human sign-off given accounting standards.
Model cost impact of sourcing decisions
Cost impact modelling for sourcing is nearly fully automated, but major sourcing decisions continue to require human strategic oversight given their commercial impact.
Build showback cost reporting
Showback reporting is entirely machine-generated and distributed, with human involvement eliminated except for rare structural changes.
Conduct budget variance analysis
Variance analysis is a fully autonomous, continuous process embedded in enterprise finance platforms with no routine human touchpoint.
Forecast cloud consumption costs
Forecasting is entirely machine-driven with self-correcting models, requiring no routine human involvement.
Displaying the top six biggest tasks, about 50% of the role. 18 in total.
Industry pace
Head of Operations Excellence · 2 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
42%
Human initiated, AI responds
53%
AI led, human oversight
5%
Lead Process Change Implementation
Leading people through operational change requires human influence, trust-building and judgement that AI cannot replicate.
Coach Operations Leaders in Continuous Improvement
Coaching and developing leadership capability is inherently relational and requires human mentorship.
Lead and Develop the Operations Excellence Leadership Team
Leadership and development of people is a fundamentally human capability not replicable by AI.
Identify and Size Improvement Opportunities
BI and Copilot tools help surface process data patterns, but the Head of Operations Excellence still frames and validates opportunity hypotheses.
Redesign Operational Processes
AI assists with process modelling and scenario simulation, but redesign choices require human creativity and contextual judgement.
Build Automation and Offshoring Business Cases
AI drafts financial models and cost-benefit templates from historical data, with the human framing assumptions and scope.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
Industry pace
Head of Operations Excellence · 3 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
30%
Human initiated, AI responds
47%
AI led, human oversight
23%
Lead Process Change Implementation
AI dashboards may track implementation milestones, but leadership of the change effort itself remains a human accountability.
Coach Operations Leaders in Continuous Improvement
While AI can supply reference material and case studies, coaching effectiveness depends on human rapport and tailored guidance.
Lead and Develop the Operations Excellence Leadership Team
AI may support performance data insights, but leading and developing the team remains a human relational task.
Identify and Size Improvement Opportunities
Wider process-mining and analytics adoption deepens AI's role in quantifying opportunities, though prioritisation remains human-led.
Redesign Operational Processes
Generative AI tools speed up drafting of redesign options across core banking and servicing platforms, while humans retain design authority.
Build Automation and Offshoring Business Cases
Enterprise AI tools generate standardised business cases autonomously using integrated cost and volume data, with human sign-off.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
Industry pace
Head of Operations Excellence · 5 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
10%
Human initiated, AI responds
47%
AI led, human oversight
38%
Fully automated
5%
Lead and Develop the Operations Excellence Leadership Team
People leadership continues to require human empathy, motivation and judgement, even as AI tools mature elsewhere in the role.
Redesign Operational Processes
AI-assisted design and simulation tools are embedded in the redesign workflow, but strategic trade-offs remain a human-led activity.
Lead Process Change Implementation
AI-based implementation tracking and risk flagging assist the leader, though the leadership role stays firmly human-led.
Coach Operations Leaders in Continuous Improvement
AI-curated learning content and performance insights support coaching conversations, but the coaching relationship remains human-led.
Identify and Size Improvement Opportunities
Mature process-mining platforms proactively surface and size opportunities across the bank's operations, with human review before action.
Build Automation and Offshoring Business Cases
Business case generation is largely automated across the bank's standard automation/offshoring templates, with human review for material decisions.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
Proactive investment
Head of Operations Excellence · 2 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
30%
Human initiated, AI responds
47%
AI led, human oversight
23%
Lead Process Change Implementation
Even with rapid AI adoption, leading people through change remains a human accountability requiring trust and influence.
Coach Operations Leaders in Continuous Improvement
Coaching remains a relational, human-led activity even as AI content tools begin to support learning material development.
Lead and Develop the Operations Excellence Leadership Team
Leading and developing people remains a distinctly human capability regardless of the pace of AI investment.
Identify and Size Improvement Opportunities
Proactive investment accelerates adoption of process-mining and AI analytics tools that surface and quantify opportunities, with the leader still validating priorities.
Redesign Operational Processes
Generative AI design tools, piloted and scaled quickly under this model, accelerate scenario generation while humans retain redesign authority.
Build Automation and Offshoring Business Cases
Enterprise and specialist AI vendors are scaled quickly to auto-generate standardised business cases from cost and volume data, with human sign-off.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
Proactive investment
Head of Operations Excellence · 3 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
14%
Human initiated, AI responds
43%
AI led, human oversight
38%
Fully automated
5%
Lead and Develop the Operations Excellence Leadership Team
AI-generated performance insights may inform development plans, but leadership and team development remain human-led.
Redesign Operational Processes
AI-assisted redesign tools become embedded across operations, offering multiple design options for human evaluation and selection.
Lead Process Change Implementation
AI-driven implementation dashboards and predictive risk flagging support the leader, though change leadership stays human-led.
Coach Operations Leaders in Continuous Improvement
AI-personalised coaching insights and performance analytics increasingly inform coaching conversations, accelerating skill development.
Identify and Size Improvement Opportunities
Scaled AI platforms autonomously scan operational data across the bank to identify and size opportunities, with human oversight on prioritisation.
Build Automation and Offshoring Business Cases
Business case generation for automation and offshoring is largely autonomous across most scenarios, with humans reviewing high-value or high-risk cases.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
Proactive investment
Head of Operations Excellence · 5 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
10%
Human initiated, AI responds
37%
AI led, human oversight
37%
Fully automated
16%
Lead and Develop the Operations Excellence Leadership Team
As AI absorbs more operational tasks, human leadership skills become even more critical for guiding teams through continued transformation.
Lead Process Change Implementation
AI tools proactively track and predict implementation risks across scaled transformation programs, augmenting but not replacing human leadership.
Coach Operations Leaders in Continuous Improvement
AI-driven coaching insights are deeply embedded in leadership development, though the coaching relationship itself remains human-led.
Identify and Size Improvement Opportunities
Opportunity identification is largely AI-driven and continuous across enterprise systems, with human involvement focused on strategic prioritisation.
Redesign Operational Processes
Mature AI design platforms propose and simulate process redesigns autonomously, with humans curating and approving final designs.
Build Automation and Offshoring Business Cases
AI systems generate and refine business cases end-to-end using live operational and financial data, with human oversight retained for governance.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
AI-first transformation
Head of Operations Excellence · 2 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
14%
Human initiated, AI responds
43%
AI led, human oversight
38%
Fully automated
5%
Lead and Develop the Operations Excellence Leadership Team
Leadership and team development remain human-only responsibilities that AI cannot replicate, regardless of automation elsewhere in the role.
Redesign Operational Processes
AI agents generate complete redesign options rapidly, but strategic and creative trade-offs still require human framing at this early stage.
Lead Process Change Implementation
AI-driven change management platforms provide predictive risk insights and automated tracking, but leading people through change remains human.
Coach Operations Leaders in Continuous Improvement
AI-generated performance insights and personalised development content substantially augment coaching, though the relationship remains human-led.
Identify and Size Improvement Opportunities
AI-first adoption embeds agents that continuously scan operational data to identify and size opportunities, with human oversight on prioritisation.
Build Automation and Offshoring Business Cases
AI agents autonomously build standardised business cases from live cost and operational data across the bank, with human sign-off for governance.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
AI-first transformation
Head of Operations Excellence · 3 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
10%
Human initiated, AI responds
37%
AI led, human oversight
30%
Fully automated
23%
Lead and Develop the Operations Excellence Leadership Team
As routine work is automated extensively, human leadership becomes even more central to guiding teams through continuous transformation.
Lead Process Change Implementation
Even in an AI-first operating model, influencing and motivating people through transformation requires human trust and leadership presence.
Coach Operations Leaders in Continuous Improvement
Even in a highly automated environment, coaching requires human empathy and judgement that AI cannot replace, though AI enriches the process.
Identify and Size Improvement Opportunities
Autonomous AI agents operate end-to-end opportunity identification workflows across the bank, with humans reviewing outputs periodically.
Redesign Operational Processes
AI autonomously proposes and simulates end-to-end process redesigns across most operations, with humans curating and approving strategic choices.
Build Automation and Offshoring Business Cases
Business case generation for automation and offshoring is fully automated end-to-end for the vast majority of scenarios given the AI-first operating model.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
AI-first transformation
Head of Operations Excellence · 5 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
10%
Human initiated, AI responds
37%
AI led, human oversight
20%
Fully automated
33%
Lead and Develop the Operations Excellence Leadership Team
People leadership persists as a distinctly human capability even within a highly automated, AI-first operating model.
Lead Process Change Implementation
AI agents manage implementation logistics and risk flagging extensively, but the human leadership role in guiding people through change persists.
Coach Operations Leaders in Continuous Improvement
AI-driven coaching insights are deeply embedded, but the mentoring relationship and trust-building remain distinctly human at this scale of transformation.
Redesign Operational Processes
Redesign generation is highly autonomous, but strategic creativity and organisational context retained by humans given the scale of transformation involved.
Identify and Size Improvement Opportunities
Opportunity identification and sizing is fully automated through embedded AI agents operating continuously across all operational systems.
Build Automation and Offshoring Business Cases
AI agents autonomously build, refine and validate business cases using real-time enterprise data, with human involvement limited to exceptional cases.
Displaying the top six biggest tasks, about 49% of the role. 17 in total.
Industry pace
Manager, Customer Marketing · 2 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
30%
Human initiated, AI responds
43%
AI led, human oversight
28%
Lead and develop campaign team
People leadership and development require human empathy, mentoring and judgement not replicable by AI.
Develop portfolio campaign plan
AI tools surface market and customer insights to inform planning, but portfolio strategy remains human-led at Noverden.
Define audience segments and suppressions
AI-assisted segmentation analytics in CRM/BI tools accelerate segment definition, but humans validate suppressions for compliance.
Design incrementality measurement
Analysts use AI-assisted statistical tools to test measurement approaches, but design logic remains human-driven.
Build multi-channel campaign briefs
Copilot and templated brief tools within M365/Salesforce generate first-draft briefs that managers review and adjust.
Report campaign performance results
BI and analytics platforms auto-generate performance reports; managers interpret and contextualise findings.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
Industry pace
Manager, Customer Marketing · 3 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
14%
Human initiated, AI responds
36%
AI led, human oversight
49%
Lead and develop campaign team
Team leadership remains a core human responsibility, with AI at most supporting administrative HR tasks.
Develop portfolio campaign plan
Deeper integration of AI scenario modelling into planning workflows accelerates option generation while humans set direction.
Design incrementality measurement
AI models propose measurement designs and test structures, requiring human validation of methodology.
Build multi-channel campaign briefs
Brief generation becomes largely automated from campaign plan inputs, with light human editing for nuance.
Define audience segments and suppressions
Automated segmentation engines apply suppression rules with human sign-off for higher-risk cohorts.
Report campaign performance results
Reporting is substantially automated with dashboards refreshing in real time, reducing manual compilation.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
Industry pace
Manager, Customer Marketing · 5 years
They do nothing deliberate, and adopt whatever their existing vendors ship.
Human only
10%
Human initiated, AI responds
20%
AI led, human oversight
48%
Fully automated
23%
Lead and develop campaign team
Leadership and coaching stay human-led even as AI tools assist with performance data and scheduling.
Develop portfolio campaign plan
Enterprise AI platforms draft portfolio plan options from performance and market data, with managers refining and approving strategy.
Define audience segments and suppressions
Segmentation is largely autonomous using integrated data platforms, with periodic human governance checks required for consumer protection.
Design incrementality measurement
AI-driven experimentation platforms automate incrementality design with human oversight on interpretation and business relevance.
Build multi-channel campaign briefs
Mature enterprise marketing platforms auto-generate multi-channel briefs directly from approved plans with minimal manual intervention.
Report campaign performance results
End-to-end automated reporting pipelines deliver performance insights directly to stakeholders with minimal manual input.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
Proactive investment
Manager, Customer Marketing · 2 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
20%
Human initiated, AI responds
30%
AI led, human oversight
49%
Lead and develop campaign team
People leadership requires human empathy and mentoring, remaining unaffected by proactive AI investment in other areas.
Develop portfolio campaign plan
Proactive AI investment gives planners richer AI-generated market and customer insight, though strategic direction is still human-set.
Design incrementality measurement
AI experimentation tools propose measurement frameworks, but analysts still validate design given proactive but still-maturing capability.
Build multi-channel campaign briefs
Enterprise and specialist AI tools generate near-complete briefs from campaign plans, requiring only manager review.
Define audience segments and suppressions
Specialist AI segmentation tools autonomously build and refine segments, with human sign-off on suppression logic for compliance.
Report campaign performance results
Advanced BI and specialist marketing analytics tools autonomously generate and distribute performance reports for manager review.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
Proactive investment
Manager, Customer Marketing · 3 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
10%
Human initiated, AI responds
20%
AI led, human oversight
48%
Fully automated
23%
Lead and develop campaign team
Team leadership stays human-led, though AI tools may support performance data analysis for coaching conversations.
Develop portfolio campaign plan
Specialist marketing AI vendors enable autonomous generation of portfolio plan drafts, with managers providing strategic direction and approval.
Define audience segments and suppressions
Segmentation and suppression rules operate largely autonomously across integrated data platforms, with periodic human governance checks.
Design incrementality measurement
Specialist measurement platforms autonomously design and execute incrementality tests, with human review of business relevance.
Build multi-channel campaign briefs
Brief generation is fully integrated into campaign orchestration platforms, requiring no routine manual drafting.
Report campaign performance results
Reporting pipelines operate fully automatically with real-time dashboards, removing manual compilation entirely.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
Proactive investment
Manager, Customer Marketing · 5 years
A deliberate AI investment programme, aimed at the highest-volume work first.
Human only
10%
Human initiated, AI responds
14%
AI led, human oversight
42%
Fully automated
34%
Lead and develop campaign team
Leadership and development remain fundamentally human even as AI reshapes much of the team's day-to-day work, requiring stronger change leadership.
Develop portfolio campaign plan
AI platforms independently produce data-driven portfolio strategies at scale, with human oversight focused on strategic fit and risk appetite.
Design incrementality measurement
AI-driven measurement science is embedded across campaigns, with humans overseeing interpretation of results for strategic decisions.
Build multi-channel campaign briefs
Multi-channel briefs are generated and distributed autonomously across the marketing technology stack with negligible human involvement.
Define audience segments and suppressions
Mature AI-driven customer data platforms manage segmentation and suppression end-to-end with governance rules embedded, minimising manual involvement.
Report campaign performance results
Performance reporting is entirely autonomous and integrated into stakeholder workflows, with insights delivered proactively by AI.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
AI-first transformation
Manager, Customer Marketing · 2 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
10%
Human initiated, AI responds
20%
AI led, human oversight
48%
Fully automated
23%
Lead and develop campaign team
People leadership remains fundamentally human, though the manager increasingly leads a smaller team overseeing AI-driven workflows.
Develop portfolio campaign plan
AI-first platforms autonomously generate data-driven portfolio plan options at scale, with the manager providing strategic direction and final approval.
Define audience segments and suppressions
AI agents autonomously build segments and apply suppression logic, with human oversight limited to periodic governance checks.
Design incrementality measurement
AI agents autonomously design and run incrementality tests, with human oversight on methodology and interpretation of results.
Build multi-channel campaign briefs
AI agents embedded in campaign platforms generate complete multi-channel briefs directly from approved plans without manual drafting.
Report campaign performance results
AI agents generate and distribute real-time performance reports autonomously across all stakeholders without manual compilation.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
AI-first transformation
Manager, Customer Marketing · 3 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
10%
Human initiated, AI responds
14%
AI led, human oversight
42%
Fully automated
34%
Lead and develop campaign team
Team leadership stays human-owned even as automation reshapes team structure and required skills significantly.
Develop portfolio campaign plan
AI agents independently synthesise market, customer and performance data into near-complete portfolio strategies, with human oversight focused on risk appetite.
Design incrementality measurement
Measurement design is largely self-optimising through AI experimentation platforms, with humans validating strategic relevance of findings.
Build multi-channel campaign briefs
Brief generation is entirely autonomous across the marketing technology stack, requiring no routine human involvement.
Define audience segments and suppressions
Segmentation and suppression are executed entirely by AI within embedded governance rules, with human review only on exception escalation.
Report campaign performance results
Performance reporting is entirely autonomous, integrated directly into stakeholder dashboards and decision systems.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
AI-first transformation
Manager, Customer Marketing · 5 years
They automate everything AI can handle and rebuild teams around what is left.
Human only
10%
Human initiated, AI responds
14%
AI led, human oversight
35%
Fully automated
41%
Lead and develop campaign team
Leadership and development remain human-only, though the role evolves toward leading smaller, highly AI-augmented teams focused on strategic and governance.
Develop portfolio campaign plan
Portfolio planning is highly autonomous end-to-end, but strategic accountability and final sign-off remain with the manager given business risk implication.
Build multi-channel campaign briefs
This administrative task is fully eliminated from human workload as AI-first orchestration handles brief creation end-to-end.
Define audience segments and suppressions
AI-driven customer data platforms manage segmentation and suppression fully autonomously with compliance rules embedded by design.
Report campaign performance results
This task is essentially eliminated from manual workload as AI delivers proactive, continuous performance insights autonomously.
Design incrementality measurement
AI systems autonomously design, execute and interpret incrementality measurement at scale, requiring human input only for strategic escalation.
Displaying the top six biggest tasks, about 46% of the role. 18 in total.
Real platform results for four sample roles, three AI adoption scenarios and three timeframes. Each assessment includes its reasoning. Percentages show each task’s approximate share of the role.
The work
Every role splits into the tasks inside it, and each task is scored on where it lands between staying human and disappearing altogether.
The scenarios
Three adoption paths across three horizons, so your client can see what happens if they move and what happens if they sit still.
The skills
Which skills matter less as the work changes, which ones to double down on, and which are new and need developing. At each horizon.
Where the ROI is
Clusters of highly automatable work, ranked by headcount, hours, frequency and how many divisions they span, with cost modelled over the top.
How you run it
Your team logs in, sets up the client and runs the analysis.
Step 1
Create your client
Tell us what they do and what sits in their technology stack.
Step 2
Set the scenarios
Whichever AI futures and roadmaps you want to test, over as many horizons as you like.
Step 3
Upload what they have
Whatever they have. An HRIS or ATS export, a role list, even goals data. It does not need to be tidy.
Step 4
Press go
Everything comes back scored. What you make of it is your engagement.
You get the scored data to build your own story on.
Why consultancies partner with GoFIGR
01
Win new business, then grow it
Turn up with evidence nobody else has and you win the work. The analysis then shows your client what else needs fixing, and you are already in the room.
02
Keep the work that follows
We don't do redesign, change, operating models or reskilling. The assessment is yours to bill for, and so is everything it opens up behind it.
03
Replace weeks of fieldwork
No interviews, no staff survey, no personal data. Your margin comes from the thinking, not the data collection.
04
Bring something your competitors can't
Readiness scores and sector benchmarks are a commodity your client can buy anywhere. Analysis of the actual work inside their own roles is not.
What's your client asking you right now?
Help your clients decide where AI can make a difference, what that means for their people and where to act first.
What you sell next
The business case, then the programme that spends it.
They get a figure they can put in a board paper and take apart line by line, because it is built up from the actual work. Someone then has to deliver against it.
What you put in front of them
Where the value sits, division by division
Every task scored and valued against their own cost base
What to do first, and what it gives back
What you sell next
The redesign, with something solid underneath it.
They find out which jobs change and which ones hold before anyone draws a new structure. Your redesign then survives a consultation process.
What you put in front of them
Every role scored on the work inside it, not the title
Which roles shift, which hold, which absorb the freed-up capacity
No interviews, no staff survey, no personal data
What you sell next
A capability programme with an actual target.
They see which skills matter less as the work changes and which new ones need developing, tied to the tasks that are actually moving.
What you put in front of them
Skills mapped to the tasks that are changing
How that picture moves at two, three and five years
Where the first dollar of the budget should go
What you sell next
Their organisation, not their industry.
It runs on their position descriptions and their structure, so the output describes their business and nobody else's. That is the part they will pay you to interpret.
What you put in front of them
Built on their own role data, not a sector average
Scenarios they can move, rather than a fixed picture
Your brand on the output, your name on the advice
Working together
You license the platform and use it inside your own engagements. Pricing runs on credits. You buy what you expect to use, and the more you buy the less each credit costs. No minimum commitment, and nothing stopping you walking away after one client.
Most firms start with a single client and decide from there.
Frequently asked questions
Curious about something else?
Drop us a question and we’ll get back to you!
No. You own the relationship. We do not contact your client, and we do not sell to them behind you.
Less than you think. An HRIS or ATS export, a role list, position descriptions, even goals data. It does not need to be clean, and it never needs names, employee records or any other personal data.
They usually have more than they think, and we can work with whatever comes out of their systems. If there is genuinely nothing, we can help build it.
Every task score traces back to the task and the assumption behind it, so you can defend any number in the room.
On credits. You buy what you expect to use, and the more you buy the less each credit costs. There is no minimum commitment, and nothing stopping you walking away after one client.
Yes. Your brand goes on the output and your name goes on the advice. We stay in the background.
Run your first client this month.
Tell us about one client and we'll run the first analysis alongside you.