First Name
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Last Name
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Company
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Country
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Email
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Timezone required
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Eastern - Asia & Middle East / Africa (AM)
Western - Americas, Europe, & Middle East / Africa (PM)
Which BEST describes your organization's experience of AI in 2025?
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Moved from pilots to scaled deployment in core workflows
Stayed in pockets, strong experimentation but limited adoption
Adoption grew, but quality, risk, or controls created friction
Focus shifted from GenAI to data foundations & governance
Other
Please specify (Other)
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Where is your LARGEST “AI readiness” gap (perception vs reality)?
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Senior leaders overestimate organizational capability and/or adoption speed
Managers want AI, but cannot translate into workflow redesign
Staff usage is high, but output quality is inconsistent
Tools exist, but data access and permissions block progress
Controls and governance are unclear, causing risk aversion
Other
Please specify (Other)
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Looking to 2026, which trend will MOST reshape work in your function?
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Stronger ROI expectations and tighter value tracking
AI agents embedded into workflows and service models
Meeting AI cybersecurity threats and resilience requirements
Data quality, lineage, and governance as a bottleneck
Geographic divergence, uneven pace across regions and entities
Other
Please specify (Other)
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Which human skills will matter MOST as AI scales?
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Judgement and decision-making under uncertainty
Problem framing and asking better questions
Client empathy, trust, and relationship depth
Influence, stakeholder management, and alignment
Storytelling and translating insight into action
Leading through change and building psychological safety
Ethical reasoning and risk ownership
Other
Please specify (Other)
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What is the LARGEST talent implication of AI for Early Careers (EC) in 2026?
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EC programs redesign to provide deliberate practice vs “osmosis learning”
Higher baseline expectations for graduates on data, quant, and tech fluency skills
New roles and pathways for Analysts as “AI enabled operators”
More structured coaching, feedback loops, and QA on outputs for EC hires
Greater focus on human skills, communication, collaboration, resilience
Other
Please specify (Other)
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What leadership shifts are MOST critical to succeed with "human plus AI teams" in 2026? (Select all that apply)
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Leaders model AI use, setting expectations and normalising experimentation
Clear accountability on who owns decisions when AI is involved
Psychological safety – teams can challenge outputs and escalate risk
Operating model redesign, with leaders sponsoring workflow and role changes
Talent and incentives focus, with performance goals reflecting adoption, quality, and control
Governance in the flow of work, embedding guardrails into processes
Client trust and ethics as a priority
Other
Please specify (Other)
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