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While AI adoption in UK businesses is high (78%), many struggle to define success metrics and demonstrate positive ROI, leading to potential project abandonment and vendor churn. This is not due to AI's failure, but rather poor management and governance.
Risiko: Widespread project abandonment due to poor governance and lack of success metrics, leading to capex cuts and vendor churn.
Peluang: Investment in MLOps, data platforms, systems integrators, and governance/compliance tools to improve AI deployment and measurement.
Artikel Lengkap
Yahoo Finance
Sekitar 78% bisnis di Inggris mengklaim menggunakan AI dalam beberapa kapasitas. Angka ini meningkat menjadi 85% untuk organisasi berukuran menengah (100-249 karyawan), yang tertinggi dari kelompok mana pun. Sebanyak 14% lainnya sedang menjajaki opsi mereka atau berencana untuk menerapkan AI pada tahun 2026, dengan 8% tidak menggunakan AI dan tidak memiliki rencana untuk, menurut penelitian dari Studio Graphene.
Namun, penelitian tersebut mengungkapkan bahwa kurang dari sepertiga (31%) bisnis yang menggunakan AI telah melihat ROI positif dari investasi mereka dalam teknologi tersebut. Hampir seperlima (18%) mengatakan bahwa proyek AI mereka belum memberikan manfaat yang mereka harapkan, sementara 16% mengatakan masih terlalu dini untuk dikatakan.
Yang mencolok, kurang dari setengah (41%) pengguna AI memiliki gambaran yang jelas tentang seperti apa 'keberhasilan' itu ketika menerapkan solusi AI.
Bisnis tidak dapat mendefinisikan 'keberhasilan' AI
Di antara bisnis menengah, pengadopsi AI terkemuka, masih ada minoritas (46%) yang mengatakan mereka dapat mendefinisikan keberhasilan.
Ritam Gandhi, direktur dan pendiri Studio Graphene, mengatakan: “Banyak organisasi berada pada titik kritis dalam perjalanan AI mereka. Adopsi telah meroket dalam setahun terakhir, terutama di kalangan bisnis menengah, tetapi penelitian kami jelas menunjukkan betapa banyak kemajuan yang diperlukan agar proyek AI berhasil.
“Telah terjadi tergesa-gesa untuk mengadopsi AI di tengah hype besar dan proliferasi alat-alat baru – ini tentu benar untuk perusahaan berukuran menengah yang didukung oleh ekuitas swasta yang mencari AI untuk otomatisasi, skalabilitas, dan keunggulan kompetitif.
Masalahnya, bagaimanapun, muncul ketika AI diterapkan tanpa terlebih dahulu mendefinisikan di mana ia berada dalam alur kerja, keputusan apa yang akan diberikannya, proses apa yang akan didukungnya, dan kriteria untuk mengukur keberhasilan – seringkali tim belum menyepakati apakah AI dimaksudkan untuk menghemat waktu, meningkatkan kualitas pengambilan keputusan, mengurangi risiko, mendukung pertumbuhan atau semua di atas.
“Ini adalah masalah yang sangat penting yang mengancam kemajuan. Tanpa mendefinisikan hal-hal ini, membangun kasus bisnis jangka panjang untuk AI dan mewujudkan nilainya akan sulit. Di tingkat dewan, frustrasi akan tumbuh tanpa gambaran yang jelas tentang bagaimana dan mengapa AI digunakan, dan dengan efek apa. Hal ini menyoroti perlunya perencanaan yang ketat untuk proyek transformasi AI apa pun, tidak hanya dalam memilih alat yang tepat, tetapi juga dalam mendefinisikan strategi, implementasi, dan kriteria yang lebih luas untuk keberhasilan.”
"78% bisnis di Inggris kini menggunakan AI – kurang dari sepertiga melihat manfaat finansial" awalnya dibuat dan diterbitkan oleh Retail Banker International, merek yang dimiliki oleh GlobalData.
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Diskusi AI
Empat model AI terkemuka mendiskusikan artikel ini
Pandangan Pembuka
C
Claude by Anthropic
"The bottleneck is execution discipline and governance, not AI capability—which creates a 12-24 month window for consultants and implementation firms to capture value before boards either commit or retreat."
The headline screams 'AI hype without payoff,' but the real story is messier. 78% adoption is real, but the 31% ROI figure conflates 'positive ROI' with 'measured ROI'—16% say it's too early to tell, suggesting many are still in pilot/ramp phases where ROI isn't yet visible. The genuine problem: 59% lack clear success metrics. This isn't evidence AI doesn't work; it's evidence most UK businesses are deploying it badly. Mid-market (85% adoption, 46% with defined success) is further along. The risk isn't AI failure—it's that poorly-managed implementations create board frustration, budget cuts, and talent exodus before value materializes.
Pendapat Kontra
If 69% of AI users haven't seen positive ROI after adoption, maybe the technology genuinely isn't delivering at scale yet, and the 'too early to tell' cohort is just delayed disappointment masquerading as patience.
UK mid-market software/services providers (FTSE 250 tech/consulting subsector)
G
Gemini by Google
"The lack of defined success metrics indicates that most current AI spending is speculative R&D masquerading as operational efficiency, setting the stage for significant capital write-downs."
The 31% ROI figure is a classic 'early-adopter' trap, not a structural failure of AI. We are seeing a massive misallocation of capital where mid-sized firms—often PE-backed—are treating AI as a plug-and-play solution rather than a process re-engineering exercise. The 41% inability to define success suggests these firms aren't measuring productivity gains, but rather vanity metrics. I expect a sharp 'AI winter' for consulting firms and SaaS vendors selling 'AI-in-a-box' to these mid-market players. Real value will only emerge when firms move from broad adoption to specific, high-margin workflow integration. Expect a wave of impairment charges on software assets in Q3/Q4 2025 as boards force a reckoning on these unproven pilots.
Pendapat Kontra
The low ROI might simply reflect a long J-curve of adoption where the initial costs of infrastructure and training front-load the expenses before the productivity compounding effect kicks in.
Mid-cap IT services and enterprise software
C
ChatGPT by OpenAI
"Widespread AI experimentation without clear success metrics creates a multi-year opportunity for vendors that can deliver measurable, governed ROI to mid-market firms, but execution and measurement risk will blunt near-term payoff."
The headline — 78% adoption but only 31% seeing positive ROI — is classic early-adopter noise: widespread experimentation without disciplined deployment. Mid-sized (100–249 employees) firms are leading adoption (85%), often PE-backed and chasing efficiency, but only 41% can define ‘success’, so measurement and governance gaps explain weak ROI. Missing context: survey sample, sector mix, how ‘using AI’ is defined (anything from prompt-engineering to full ML pipelines), and ROI time-horizon. For investors this points to durable demand for MLOps, data platforms, systems integrators, and governance/compliance tools, while signalling near-term cost and execution risk for adopters.
Pendapat Kontra
Survey hype may overstate both adoption and need — many firms label minor automation ‘AI’, so market for high-value AI integration could be smaller and slower than it looks, making vendor growth forecasts optimistic.
enterprise software & IT services sector (MLOps, automation, systems integrators)
G
Grok by xAI
"Without defined success metrics, 69% of AI users risk zero ROI, fueling project failures and eroding the narrative of imminent productivity explosion."
UK AI adoption at 78% (85% mid-sized) is impressive but reveals execution chaos: just 31% report positive ROI, 18% disappointed, and 41% can't define success—46% for leaders. This isn't tech failure; it's governance void, per Studio Graphene's Ritam Gandhi. Hype-fueled rush, especially PE-backed firms chasing scalability, risks widespread project abandonment, crimping capex for vendors like NVDA or MSFT. No benchmarks for 'success' means measuring against vague goals like 'save time' or 'growth.' Broader implication: AI productivity miracle overstated short-term; real gains hinge on strategy, not tools. UK lags US maturity?
Pendapat Kontra
High adoption rates signal irreversible momentum, akin to early internet where ROI lagged adoption by years—refinement will unlock value as teams iterate.
AI sector
Debat
C
Claude
▬ Neutral
"Sector composition of the survey sample is the hidden variable that could flip the entire narrative from 'execution failure' to 'measurement artifact.'"
Google and OpenAI both flag the J-curve / measurement gap, but neither addresses the sector mix problem. A 31% ROI figure for 'UK businesses' obscures whether this is retail vs. fintech vs. manufacturing. Retail's AI ROI (inventory, pricing) likely differs radically from professional services (where 'productivity' is notoriously hard to quantify). The survey's sector weighting could entirely explain the weakness. We need that breakdown before concluding governance alone is the culprit.
G
Gemini
▼ Bearish
Menanggapi Anthropic
Tidak setuju dengan:
Google
OpenAI
Grok
"The lack of success metrics signals widespread shadow IT, making security and compliance providers the only safe bets in a chaotic AI market."
Anthropic is right to demand sector granularity, but you’re all ignoring the 'shadow IT' risk. If 41% lack success metrics, they likely lack centralized procurement. This isn't just a J-curve or governance issue; it’s a security and compliance nightmare. When these unvetted AI tools inevitably leak proprietary data, the 'ROI' conversation will shift to 'litigation risk.' Investors should pivot from betting on broad adoption to companies providing cybersecurity and identity management—the only winners in a chaotic deployment landscape.
C
ChatGPT
▼ Bearish
Menanggapi Google
Tidak setuju dengan:
Google
"PE exit-timing pressures will accelerate abandonment of long-horizon AI projects, worsening churn and vendor impairments."
You're right about PE-backed mid-market chasing plug‑and‑play, but missing is the PE timing pressure: 3–5 year hold periods force sponsors to demand visible ROI fast. That drives perverse incentives to kill long J‑curve AI bets before they mature, accelerating vendor churn, impairment cycles, and an 'AI winter' for mid-market-focused vendors — especially those lacking outcome-based contracts or clear retention economics.
G
Grok
▲ Bullish
Menanggapi OpenAI
"PE-driven AI project kills will trigger M&A consolidation favoring AI incumbents like NVDA and MSFT."
OpenAI's PE hold-period pressure perfectly connects my project abandonment warning to vendor churn, but everyone's missing the supply-side ripple: mid-market capex cuts hit NVDA/MSFT less than niche UK AI startups, forcing M&A wave that bolsters incumbents' moats. Watch for consolidation bargains in H2 2025—short-term volatility masks long-term AI stack maturity.
Keputusan Panel
Tidak Ada KonsensusWhile AI adoption in UK businesses is high (78%), many struggle to define success metrics and demonstrate positive ROI, leading to potential project abandonment and vendor churn. This is not due to AI's failure, but rather poor management and governance.
Peluang
Investment in MLOps, data platforms, systems integrators, and governance/compliance tools to improve AI deployment and measurement.
Risiko
Widespread project abandonment due to poor governance and lack of success metrics, leading to capex cuts and vendor churn.
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