Transformative AI: Maximising efficiency while minimising carbon
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Key report insights
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AI drives operational efficiency:
73% of retailers report that AI is already helping them identify operational inefficiencies, reducing waste, optimising supply chains, and minimising carbon emissions.
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Sustainability and profitability go hand in hand:
Retailers that embraced AI-driven sustainability practices saw profit margins grow 92% over five years while carbon intensity fell by 24.6%. This demonstrates that environmental responsibility doesn't come at the expense of profitability.
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The customer experience is being redefined:
61.5% of consumers say personalised recommendations are critical to their shopping journey, while 60.1% prioritise seamless returns—both of which are being revolutionised by AI tools.
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AI adoption varies by country:
French retailers lead in recognising AI's benefits, particularly in personalisation and sustainability, while Canadian retailers remain more cautious due to limited commercial applications of AI.
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Retail functions experience uneven AI impact:
While merchandising and marketing is the most impacted function today, sustainability and waste management is expected to see the biggest growth in the next two years.
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Consumer expectations are shifting:
Over 90% of under-35s engage with circular economy initiatives such as product buy-back schemes, rental models, and pre-loved goods—highlighting the growing influence of sustainability on purchasing decisions.
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Barriers remain, but opportunities abound:
Retailers cite data availability (34%) and system integration challenges (33%) as major barriers to AI adoption. Yet, companies that invest early are poised to lead in both customer experience innovation and cost reduction.
AI: Shaping the evolution of retail
Retail is entering a new era—one where AI-driven insights are unlocking operational efficiencies while reshaping customer journeys. From the initial point of awareness to post-purchase engagement, AI is transforming every touchpoint.
Our research reveals that:
🔹 61.5% of consumers value personalised product recommendations during the awareness stage.
🔹 66.5% expect real-time stock visibility when researching products.
🔹 60.1% prioritise hassle-free returns, highlighting the growing demand for seamless aftersales experiences.
AI doesn’t just personalise interactions—it synchronises retail channels into a unified commerce environment. By analysing vast datasets in real-time, AI empowers businesses to anticipate consumer needs, streamline operations, and minimise environmental impact.
From AI-powered product discovery tools to sustainable delivery route optimisation, technology is redefining what’s possible. As retailers integrate these capabilities, they’ll build stronger customer relationships while paving the way for long-term growth.
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AI: Transforming retail from both sides of the till
AI is reshaping retail at an unprecedented scale, delivering benefits that span both consumer-facing experiences and back-end operations. From hyper-personalised marketing to intelligent supply chain optimisation, AI is transforming how retailers engage customers, manage resources, and drive growth.
Our research reveals that businesses leveraging AI are not only improving efficiency but also aligning profitability with sustainability goals. By tapping into real-time data analytics, retailers can streamline processes while minimising environmental impact.
Consumer-centric AI innovations
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Personalised product discovery: 61.5% of consumers consider tailored recommendations essential to their shopping experience.
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Frictionless in-store interactions: 65.7% of consumers want knowledgeable staff—AI-powered tools provide instant product insights.
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Sustainability-focused shopping: 70% of consumers appreciate carbon footprint data on product labels.
Operational efficiencies behind the scenes
AI isn't just revolutionising customer interactions—it’s also streamlining core retail operations. Key improvements include:
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Demand forecasting breakthroughs: AI-driven models help retailers predict demand fluctuations, reducing inventory waste by up to 20%.
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Dynamic pricing strategies: AI algorithms adjust prices in real-time, responding to market dynamics and driving sales uplift of 15%.
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Sustainable delivery solutions: AI-powered logistics tools cut transport emissions by 14% through optimised delivery routes.
Sustainability and profitability: A complementary relationship
Our research found that retailers who prioritise AI-driven sustainability initiatives achieved 92% profit growth over five years, while cutting carbon intensity by 24.6%. This demonstrates that environmental responsibility and profitability can coexist.
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Strategic priorities for maximising AI investment in retail
As AI adoption accelerates, retailers must act decisively to unlock its full potential. Our research identifies four key strategic priorities for businesses looking to harness AI’s transformative power. These priorities offer a practical roadmap for aligning AI with operational goals, sustainability targets, and customer engagement strategies.
AI is more than a technology—it’s a catalyst for operational reinvention. By focusing on digital infrastructure, workforce development, governance frameworks, and continuous improvement, retailers can future-proof their operations and drive long-term growth.
1️⃣ Establish a strong digital core
AI’s effectiveness depends on high-quality, structured data. A strong digital core ensures seamless integration of AI applications across business functions, delivering real-time insights that optimise everything from product recommendations to inventory management.
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73% of retailers highlight that data availability and quality issues are primary barriers to AI success.
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Unified data platforms improve customer targeting, streamline marketing, and reduce operational friction.
2️⃣ Reinvent talent and ways of working
AI-driven transformation requires a digitally literate workforce. However, 64% of retailers cite skills gaps as a significant challenge. Many lack specialised AI expertise, slowing down deployment and limiting impact.
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Targeted upskilling: Ensures teams can manage AI applications across marketing, logistics, and customer-facing functions.
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Cross-functional collaboration: Aligning data scientists, marketers, and analysts for holistic AI adoption.
3️⃣ Governance of change
With AI’s rapid adoption comes heightened scrutiny over data privacy, bias, and ethical use. Our research shows that 45.1% of consumers worry about how AI systems handle personal information.
4️⃣ Embed continuous improvement
AI innovation is dynamic—models must evolve alongside shifting consumer behaviours and technological advancements. Our research found that 58% of retailers are investing in model retraining to improve forecasting accuracy.
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