This guide frames a professional listicle for investors seeking clear, practical direction on tech and stock selection. It explains why sector innovation and services-led models can deliver steady growth across cycles and why discipline matters when markets run hot.
We set expectations on how companies are assessed across value, growth and momentum. That blend helps avoid overpaying for a popular name during frothy rallies. Morningstar data, XLK moves and mega-cap gains from Nvidia and Microsoft underline current market leadership by AI and cloud.
Readers will see that companies span software, cloud, semiconductors and information services, each with distinct revenue drivers and risk. Our methodology pairs moat and valuation checks with growth and momentum screens to anchor choices in fundamentals and price action.
Next we lay out a market snapshot, selection process and practical picks for undervalued ideas, AI leaders, value options and fast growers, plus portfolio construction tips for varied time horizons.
Present market snapshot: tech outperformance and AI momentum
Recent market moves show sector leadership concentrated in large platforms as macro signals and adoption trends align.
XLK highs and macro drivers
In July, XLK rose about 4% to hit all‑time highs, helped by clearer trade talks and hopes for Fed rate cuts as early as September.
Those forces stretched multiples and broadened market breadth across computing and cloud names.
Mega-cap catalysts versus next‑gen challengers
Artificial intelligence leadership is a structural growth engine. Nvidia and Microsoft topped $4 trillion, while the Morningstar Next Generation AI Index returned 26.65% YTD through 15 Aug 2025.
Large platforms accelerate adoption across business systems, yet challengers in data engineering, edge compute and vertical software offer disruptive upside.
- Capital flows favour infrastructure and software innovation, but valuations remain sensitive to policy and earnings.
- Key trends: rising cloud workloads, edge use cases and developer platforms that scale companies efficiently.
Investors should track operating leverage, free cash flow conversion and balance‑sheet strength as growth expectations stay high and value dispersion persists.
How we selected these tech stocks today
Our selection process blends quantitative screens with qualitative checks so each pick rests on measurable signals and business quality.
Undervaluation, moats, and uncertainty screens (per Morningstar)
Morningstar anchors the first pass. We screen for price versus fair value discounts to surface clear value opportunities with identifiable moats.
Moat ratings and lower uncertainty scores help investors see durability and downside ranges for each company.
Value, growth, and momentum lenses (per Investopedia’s latest data)
Investopedia’s lists help capture rapid growth and momentum leaders. Examples include names with extreme EPS and revenue gains or big 12‑month returns.
We treat these as high‑reward but higher‑risk signals that must align with fundamentals.
“Valuation discipline beats enthusiasm when pace of adoption outstrips profit conversion.”
| Screen | Primary signal | Example metric | Use case |
|---|---|---|---|
| Morningstar | Price/Fair value | P/FV discount | Find undervalued platforms |
| Moat & Uncertainty | Economic moat, risk | Narrow/Wide; Uncertainty rating | Gauge durability |
| Investopedia | Growth & Momentum | EPS %, Revenue %, 12‑mo return | Spot accelerators |
Triangulation rule: we combine fundamentals, valuation and price action. Services and software firms get priority when recurring revenue and switching costs improve predictability.
Result: a balanced set that mixes established platforms with emerging names, favouring clear catalysts and cash‑flow progress before a buy decision.
Undervalued technology stocks to consider now
Selective picks combine systems-level advantages, recurring services and clear catalysts that could close per share gaps to fair value. Each firm below trades at a material discount per Morningstar while retaining business quality and identifiable upside paths.
Endava (DAVA)
Digital engineering specialist with deep financial services exposure. Morningstar shows a steep price/fair value gap; normalising demand and payment systems work could lift revenue and margins.
Globant (GLOB)
Studio-led engineering and cloud delivery via a nearshore network. Concentrated client mix supports scalable growth while operating leverage targets improve value.
Nice (NICE)
Leader in CXone CCaaS with an AI roadmap and compliance tools that aid enterprise adoption. Recurring licence and services revenue support margin expansion.
Sabre (SABR)
GDS network effects and airline systems integration underpin durable bookings. SabreMosaic AI and cloud migration should boost merchandising and ancillary revenue.
Akamai (AKAM)
Pivot from CDN toward security and edge computing. A broad edge network defends margins and unlocks new systems and services sales.
Sensata (ST)
Sensor content gains across EV and industrial programmes. Long OEM cycles give resilient revenue visibility as platform content rises.
HubSpot (HUBS)
Multi-hub software platform expands ARPU through freemium funnels and cross-sell. Higher per-customer spend lifts margins over time.
Adobe (ADBE)
Wide moat across content and document clouds plus generative intelligence via Firefly. Cross-cloud monetisation supports durable revenue growth.
- Business model quality: recurring software and services, sticky systems, and switching costs.
- Catalysts: margin expansion, mix shift to higher-value solutions and material customer wins that could narrow value gaps.
Best AI stocks to invest in now
Firms that combine scale, model access and repeatable revenue tend to lead adoption and profit conversion. Below we highlight names that mix platform depth with clear catalysts and Morningstar ratings.
Microsoft (MSFT)
Azure scale and OpenAI integration drive feature roll‑outs and higher ARPU. Azure growth and cross‑sell lift operating margin over time. Morningstar notes a wide moat with mid uncertainty and a modest discount to fair value.
Alphabet (GOOGL)
AI improves search relevance and ad efficiency while Google Cloud scales. That combination fuels better monetisation and resilience across core ad and cloud revenue lines.
Taiwan Semiconductor (TSMC)
TSMC supplies leading‑edge nodes that power AI training and inference. Its systems‑level role underpins long-term demand for advanced computing chips.
| Company | Moat | Primary AI edge |
|---|---|---|
| Microsoft | Wide | Azure + OpenAI |
| Alphabet | Wide | Search + Cloud AI |
| TSMC | Wide | Leading nodes for AI |
Value opportunities: tech stocks trading at compelling valuations
A focused value screen can surface smaller names that trade at single‑digit earnings multiples despite solid business models.
We assess value through low price-to-earnings ratios versus peers and fundamentals, then check product roadmaps, customer mix and cash flow. Below are three notable, inexpensive opportunities with distinct catalysts.
Yiren Digital (YRD)
Price $6.02, market cap $0.5B, trailing P/E 2.8. Yiren is an AI-enabled financial services platform that bundles insurance brokerage and lifestyle offerings.
New aviation insurance products and cross-sell could diversify revenue and support growth while keeping services sticky.
Sohu.com (SOHU)
Price $14.94, market cap $0.5B, P/E 4.0. Sohu’s revenues rely heavily on online games (87% Q1 2025), which can generate strong cash and optionality for reinvestment.
Smaller scale and limited coverage often leave such companies undervalued relative to peers.
Consensus Cloud Solutions (CCSI)
Price $21.47, market cap $0.4B, P/E 5.0. This company offers secure cloud communications, data extraction and digital signature software.
Two new credit facilities totalling $225m improve go‑to‑market firepower and product roll‑out speed.
- Due diligence: focus on data quality, customer concentration and margin sustainability.
- Risks: liquidity and volatility mean position sizing should be conservative.
- Potential: cross‑sell between cloud and software can deepen customer relationships and lift long‑term returns.
Fastest-growing tech names: revenue and EPS acceleration
This small set highlights companies with the fastest recent growth in both top‑line and per‑share profit. We screened for revenue acceleration plus EPS expansion over the most recent year and then checked durability signals such as customer retention and capital efficiency.
Innodata (INOD)
Profile: price $49.45, market cap $1.6B; EPS growth 626%, revenue growth 290%.
Why it stands out: Innodata supplies high‑quality training data and services for generative artificial intelligence model building. Its platform and engineering services underpin repeatable sales and sustained revenue momentum.
Sezzle (SEZL)
Profile: price $146.49, market cap $4.9B; EPS growth 347%, revenue growth 123%.
Why it stands out: Sezzle’s BNPL model has evolved toward higher take‑rates and operating leverage. Risk management and improved repayments drove a sharp earnings inflection in Q1 2025.
Gorilla Technology (GRRR)
Profile: price $17.33, market cap $0.4B; EPS growth 98%, revenue growth 290%.
Why it stands out: A diversified services and platform catalogue across security, network and business intelligence. Its $5.6B pipeline supports ambitious contract targets through mid‑2026.
- Methodology: combine twelve‑month revenue growth with EPS expansion and check cohort, churn and customer acquisition cost trends.
- Risk note: rapid growth can stretch multiples if demand proves cyclical or capital intensity rises.
- Catalysts: contract wins, product roll‑outs and geographic expansion can validate forecasts and lift market sentiment.
Governance and disclosure matter for smaller high‑growth companies. Use disciplined entry and exit rules and monitor cohort behaviour to judge quality of expansion.
Further reading on fast growers
High-momentum tech stocks to watch
Momentum-led names can outpace peers when revenue, orders or margins accelerate. These winners reward discipline when traders verify fundamentals and liquidity.
Quantum Computing (QUBT): integrated photonics and platform gains
Price $16.15, market cap $2.6B, 12‑month total return +2,275%. QUBT builds photonics-based platforms that advance computing systems. Sector forecasts show a rise from $15B (2024) to $38B (2029), a strong tailwind for platform adoption.
Sezzle (SEZL): sustained outperformance and operating improvement
Price $146.49, market cap $4.9B, 12‑month total return +937%. Momentum reflects better unit economics and margin progress. Market recognition has followed durable revenue and payout trends.
TSS (TSSI): data centre services capturing AI demand
Price $27.26, market cap $0.7B, 12‑month total return +840%. TSS offers integrated data centre design, configuration and maintenance services. That positions it to benefit from AI infrastructure build‑out.
| Company | Price | Market cap | 12‑mo return |
|---|---|---|---|
| Quantum Computing (QUBT) | $16.15 | $2.6B | +2,275% |
| Sezzle (SEZL) | $146.49 | $4.9B | +937% |
| TSS (TSSI) | $27.26 | $0.7B | +840% |
Risk note: rapid price gains can outpace value; use position sizing and stop rules. Watch liquidity, insider moves and catalysts that sustain or reverse momentum.
“Combine technical signals with revenue, margin or order growth to confirm durable momentum.”
Cloud computing and edge: platforms enabling durable growth
Cloud and edge platforms now form the backbone for modern business applications and AI services. They deliver workload agility, cost efficiency and scalable services that support multi-year growth across sectors.
Akamai’s distributed network, security and developer-friendly compute
Akamai has shifted from CDN-led revenue to a security-first model. Security solutions now exceed half of sales, while CDN remains about a third.
Linode and a 4,300+ point-of-presence network let Akamai offer low-latency edge computing and developer tooling that speed product roll‑outs and reduce latency for global users.
Google Cloud and Azure: workloads, data and AI service adoption
Google Cloud and Microsoft Azure capture core workloads, data services and AI adoption. Azure is roughly a $75bn business growing near 30% annually and benefits from hybrid integration and enterprise tooling.
These hyperscalers combine scale, network reach and developer ecosystems that lower time to market and expand addressable markets.
- Business notes: evaluate total cost of ownership, performance SLAs and compliance for regulated industries.
- Market impact: multi-cloud strategies boost resilience and negotiation leverage while demand for data-intensive apps drives steady platform growth.
Software and platforms with recurring revenues
Subscription-based models give software firms clearer revenue visibility and smoother cash flows than one-off licensing. This predictability boosts valuation and lets management fund growth without sudden capital raises.
HubSpot’s freemium funnel and multi-hub upsell
HubSpot runs a freemium growth model across five hubs for marketing, sales, service, operations and CMS. Roughly 15% of free users convert, and about 60% adopt multiple hubs.
Multi-hub adoption raises ARPU and improves retention. Upmarket moves add larger contracts and reduce churn, which lifts lifetime value and supports operating leverage.
Adobe Creative, Document, and Experience Clouds driving subscription value
Adobe dominates content creation via Creative Cloud while Document Cloud approaches ~$4bn and Experience Cloud grows through acquisitions. Firefly AI and Express widen the funnel and aid cross-sell.
Integrated workflows bind customers into longer relationships. That makes switching costly and lets pricing reflect clear product value for SMBs and enterprise clients.
| Metric | Why it matters | Target |
|---|---|---|
| Net revenue retention | Shows cross-sell and churn impact | >100% |
| Gross margin | Drives free cash flow and reinvestment | High, >70% |
| Operating leverage | Indicates profit scaling as revenue grows | Improving year-on-year |
Product innovation—notably AI features—keeps subscription value high and reduces churn. Strong customer success, tight integrations and tiered pricing align value with willingness to pay and help companies manage macro volatility while compounding growth over time.
Semiconductors and systems: the AI hardware backbone
Chips and foundries form the silent engine behind data‑heavy computing workloads. Semiconductors enable faster model training and more efficient inference, lowering energy per operation and shortening iteration cycles for researchers and engineers.
TSMC holds mid‑60s foundry share and stands as one of two makers at leading‑edge nodes. Its logic‑first strategy lets key customers ramp advanced chips quickly, supporting multi‑decade growth from AI, IoT and HPC demand.
Process leadership and market dynamics
TSMC’s process roadmap drives capacity intensity and long lead times. Foundry models depend on utilisation cycles and a concentrated customer mix that ties factory throughput to programme wins.
Investors should weigh long‑term demand against cyclical supply expansions. TSMC appears near 22% undervalued versus a $306 fair value estimate, yet policy and geographic factors can shift capital allocation and supply chains.
Portfolio note: exposure across the semiconductor value chain offers diversification benefits. Catalysts include new node ramps, customer programme wins and strengthened pricing power through long contracts and collaborative development that embed chips into complete systems and content.
Information technology services: digital transformation and AI delivery
Modern IT services combine consulting, hands-on engineering and managed support to move pilots into production and drive measurable business outcomes.
How they operate: strategy teams design roadmaps, engineering squads build platforms and managed services keep systems reliable while clients scale AI use cases.
Endava: nearshore engineering and sector focus
Endava leverages nearshore centres to deliver digital engineering efficiently for financial services and TMT. That model supports tight customer collaboration and targets ~20% organic growth and ~20% adjusted PBT margins.
Globant: studios for rapid iteration
Globant organises teams into studios that specialise by domain. This structure speeds delivery for media and financial clients and pursues growth several times the broader IT market while targeting a ~17% non‑GAAP operating margin.
Cognizant: consulting and AI services at scale
Cognizant blends modern consulting with AI engineering and managed offerings to capture long‑tailed enterprise demand. Shares trade below fair value, and the firm uses switching costs and technical depth to expand revenue via large accounts and cross‑sell.
- Revenue drivers: large account expansion, new logo wins and higher‑value cross‑sell.
- Margins: tied to utilisation, pricing mix and delivery location.
- Market dynamic: competition spans global integrators and niche specialists; long customer relationships remain critical for pipeline sustainment.
Key risks for tech investors: valuation, regulation, and volatility
When hype outpaces fundamentals, multiple compression can follow fast and hard.
Multiple compression risk can hit when growth expectations slip or macro conditions tighten.
Rapidly rising prices embed future gains. If revenue or profit misses occur, multiples often shrink quickly.
Volatility drivers include short product cycles, disruptive entrants and binary event risk around launches or contracts.
Smaller companies face larger swings and liquidity gaps that worsen drawdowns.
Regulatory overhangs such as data privacy, antitrust actions and cybersecurity mandates raise compliance cost and alter market structure.
Changes in rules can reduce addressable markets or force product redesigns.
Information risks come from limited disclosure or complex revenue models that impede valuation clarity.
Scenario planning and sensitivity analysis help investors stress-test key operating drivers and spot structural versus cyclical issues.
| Risk category | Potential impact | Mitigant |
|---|---|---|
| Valuation | Multiple compression, price drawdown | Buy on evidence of cash flow and margin progress |
| Regulatory | Revenue hit, higher costs | Prefer firms with compliance track record |
| Liquidity & information | Large swings, unclear forecasts | Smaller position sizing, seek transparency |
“Distinguish cyclical setbacks from structural erosion; balance exposure across cloud, AI, software and semiconductors.”
- Stress governance, capital allocation and reporting quality when selecting companies.
- Diversify across sub-sectors to reduce idiosyncratic risk.
- Monitor innovation cadence and competitive intensity for early warning signs.
Portfolio strategy: balancing growth, value, and momentum in tech
Crafting a coherent portfolio means matching allocation with objectives, risk tolerance and time horizon. A clear framework helps investors act when market moves feel sudden or confusing.
Allocate across three sleeves: a core growth sleeve for high‑quality, expanding businesses; a value sleeve for low‑multiple opportunities with improving fundamentals; and a tactical momentum sleeve for shorter‑term upside. Typical splits might be 50/30/20 for long‑term investors, adjustable by risk profile.
Position sizing, time horizons, and earnings discipline
Size positions by conviction: larger weights for robust data on revenue, margins and order books; smaller sizes where visibility is limited. Use earnings cadence and thesis milestones as decision points rather than price noise.
Rebalance on event triggers: results that confirm thesis, meaningful upgrades or persistent misses. Set explicit stop‑loss rules or hedge layers for volatile holdings.
Diversifying across AI, cloud computing, software, and semiconductors
Diversify by sub‑sector to reduce correlation. AI and semiconductors capture hardware cycles and model demand, while cloud computing and software offer recurring services and systems revenue.
Use momentum tactically—examples such as QUBT (+2,275%), SEZL (+937%) and TSS (+840%) show rapid moves, but anchor the core with value names like YRD (P/E 2.8) and CCSI (P/E 5.0) and growth leaders such as INOD (EPS +626%, revenue +290%).
“Rotate capital from stretched winners into mispriced opportunities only when improving fundamentals and data support the shift.”
- Systematically evaluate data signals: revenue, gross margin and backlog trends.
- Keep cash reserves for dislocations and tactical entries.
- Review theses periodically and run post‑mortems on major trades.
what are the best technology stocks to invest in right now?
This shortlist blends durable platform leaders with value plays that trade well below implied per share fair value.
Core picks
Microsoft — Azure scale and OpenAI ties support higher ARPU and margin expansion (≈13% below $600 fair value).
Alphabet — AI upgrades in Search and GCP should lift monetisation (≈14% below $237 fair value).
TSMC — leading‑edge nodes underpin durable demand and capacity-led upside (≈22% below $306 fair value).
Adobe — cross‑cloud content and Firefly boost subscription value (≈37% below $560 fair value).
Akamai — security and edge compute diversify revenue; resilient cash flows at 0.61 P/FV.
Contrarian / value angles
Endava, Globant, Nice and Sensata trade at material discounts versus peers. Yiren Digital trades at ~P/E 2.8. These names offer asymmetric upside if execution holds.
Portfolio note: blend core holdings for stability and smaller value positions sized modestly. Watch product releases, capacity ramps and enterprise wins as catalysts.
Morningstar top picks provide further context on valuation and moat assessments.
Conclusion
Selective exposure to platforms, cloud and subscription services can compound returns over years.
For investors, discipline matters: pair quality business models with sensible price checks and clear share catalysts. Market breadth is healthy, yet valuations often reflect lofty expectations.
Balance growth and value by blending durable software and services leaders with modestly sized value positions and a tactical momentum sleeve. Subscription models provide defensive cash flow through cycles.
Watch emerging areas such as AI, video and edge compute for long-term upside, and keep position sizing tied to thesis milestones. Rebalance periodically to capture gains and redeploy into underappreciated ideas.
Bottom line: disciplined selection across tech sub-sectors can drive compounding capital while managing risk over the years.
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