You win government contracts by doing three things better than everyone else: picking the right tenders, qualifying brutally, and submitting a clear, evidence-based bid — and in 2026, the teams that win most consistently are using AI to find, score, and write those bids faster than humans alone ever could.

Quick answer (for people who have a tender open right now)

To win government contracts, you need to:

1. Get contract-ready – have your policies, certifications, and case studies in place before you see an opportunity.

2. Target only winnable tenders – filter by size, scope, region, and fit so you’re not burning weeks on long-shot bids.

3. Understand the scoring – write every answer to maximise the evaluation score, not to “sound good”.

4. Use AI tools to do the heavy lifting – let platforms like Skim scan 4,500+ portals, summarise RFPs, suggest bid/no-bid, and draft answers from your past submissions.

5. Turn each bid into training data – build a reusable library of answers, lessons, and feedback so your win rate improves over time.

Key takeaways

• “How to win government contracts” is one of the most searched phrases in this space — and most content is still generic, offline, and pre-AI. That’s your opening.

• The public sector is huge: UK spend alone is ~£300bn a year; the EU public procurement market is close to €2 trillion.

• The real advantage is not “secret tricks” — it’s better selection, better process, and better tooling.

• AI tender platforms like justskim.ai now scan thousands of EU and UK government portals, judge tenders on likelihood of winning, and generate draft RFP responses in minutes.

• If you’re still manually checking portals and writing every answer from scratch, you’re competing with teams who have a robot bid manager as a teammate.

Why government contracts feel hard to win (and what’s changed)

Government contracts look intimidating for three reasons:

1. Complex rules and portals – multiple platforms (TED, Find a Tender, Contracts Finder, national and local portals).

2. Heavy compliance – procurement rules, frameworks, social value, ESG, data protection.

3. Time-consuming bids – 80-page RFPs, multiple attachments, and strict word limits.

At the same time, governments are actively trying to get more SMEs into the game and publishing guides on “how to bid for government contracts as an SME”.

So the opportunity is massive — but only if you build a system that:

• Spots the right tenders early

• Qualifies them fast

• Produces consistently high-scoring bids

That’s what this playbook is about.

Step 1: Understand how buyers actually decide

Most contracts are awarded using some version of “Most Economically / Advantageously Tender” — a balance of quality, price, and social value, scored against published criteria.

That means:

• Every answer is scored. If there’s 10 points available and you’re not writing to hit all 10, you’re gifting the contract to someone else.

• Lowest price rarely wins alone. Buyers care about risk, delivery, and policy compliance as much as day-one cost.

• Clarity beats creativity. Evaluators are reading dozens of responses under time pressure. Short, evidence-based answers win.

Before you write anything, ask:

“If I were marking this answer with a score sheet in front of me, what would full marks look like?”

Then write to that.

Step 2: Get “tender-ready” before you chase opportunities

The biggest mistake new suppliers make is trying to assemble everything after the tender drops.

Instead, build a bid-ready foundation:

1. Core documents & policies
Buyers often expect, at minimum:

• Company registration, accounts, and tax compliance

• Insurance certificates (public, employer’s, professional where relevant)

• Health & Safety, Data Protection/GDPR, Equality & Diversity, Environmental policies

• Cyber security certifications where applicable (e.g. Cyber Essentials in the UK)

2. Case studies & references

For each past project:

• Problem → your solution → measurable outcome

• Contract value, duration, and scope

• Contactable reference where possible

3. A basic tender library

• Standard company description (short/medium/long versions)

• Team bios

• Core technical approach descriptions

• Key policies in clean, reusable formats

This is the content your AI tools will later reuse and adapt. The better your raw material, the better your bids.

Step 3: Choose the right keyword — and the right tenders

From a search perspective, “how to win government contracts” is the flagship phrase in this space. It’s broad, high-intent, and used by SMEs, consultants and mid-market suppliers across regions.

From a sales perspective, the same idea applies to tenders:

You don’t want “all tenders”. You want the specific contracts you can realistically win.

That means filtering by:

• Region & jurisdiction – EU, UK, specific countries or authorities

• Contract size – big enough to be worth it, small enough that you’re credible

• Category / CPV codes – aligned to your real capabilities

• Languages & delivery footprint

This is where AI tools change the game.

Platforms like Skim automatically:

• Scan 4,500+ government portals across Europe and the UK

• Analyse millions of contracts each year

• Match tenders to your profile and sector

• Judge each tender on your likelihood of winning

Instead of “check 10 portals every morning”, your job becomes “review today’s short-listed tenders in one dashboard”.

Step 4: Build a ruthless bid / no-bid framework

Most teams don’t lose because they’re bad at writing.

They lose because they’re bidding on everything.

Create a simple scoring grid for each opportunity:

1. Strategic fit (0–3) – Does this contract align with your core offer and long-term plan?

2. Capability (0–3) – Do you have recent, relevant experience at similar value and complexity?

3. Relationship (0–2) – Do you know the buyer or have a credible partner who does?

4. Capacity (0–2) – Can you deliver without breaking existing commitments?

Set a minimum score (e.g. 7/10) to proceed.

Then plug this into your tooling:

• Skim’s AI bid/no-bid feature can read tender documents and, using models like TenderGPT, flag red lines (mandatory criteria, financial thresholds, certifications) and suggest whether it’s worth your time.

The goal: fewer submissions, higher win rate — not more activity.

Step 5: Use AI to write score-maximising answers, not waffle

When you open the tender documents, resist the urge to start typing in the portal.

Instead:

1. Start with the evaluation criteria

   • Copy the question and its scoring scheme into your workspace.

   • Highlight every requirement, verb, and “must”.

2. Pull relevant material from your tender library

   • Past answers, case studies, policies.

   • Skim can search across your historic RFPs and suggest relevant paragraphs in seconds.

3. Let AI draft, then you edit

   With an AI RFP writer trained on your previous bids:

   • Generate a first draft for each question in your tone of voice.

   • Ensure it explicitly addresses each scoring point.

   • Cut anything that doesn’t earn marks.

   Skim’s own users report going from days of manual drafting to minutes per question once their library is in place.

4. Answer like an evaluator

   A simple, repeatable structure:

   • Promise: “We will [do X outcome] by [date / milestone].”

   • Plan: Step-by-step approach, aligned to their process.

   • Proof: Case study, metrics, references.

   • Risk: How you’ll mitigate the buyer’s concerns.

   Keep sentences short, avoid jargon, and always link your answer back to the buyer’s objectives — not your internal buzzwords.

Step 6: Price to win, not to come second

Pricing is where good bids quietly die.

A few principles from experienced government contractors:

• Know the weighting. If quality is 70% and price 30%, don’t destroy your margin chasing the lowest number.

• Model your real delivery cost. Include risk, contingencies, and overheads — governments expect sustainability, not suicide bids.

• Explain your price. Use clear breakdowns and justify value (service levels, innovation, social value).

• Avoid “hope pricing”. If the only way to “win” is a price you can’t deliver at, treat it as a no-bid.

AI can’t decide your margin, but it can:

• Compare pricing structures from previous tenders you’ve submitted

• Flag where your assumptions differ from similar, successful bids

Again, the pattern: humans decide, AI does the legwork.

Step 7: Turn every contract into future wins

Win or lose, every tender is data.

To build compounding advantage:

1. Capture everything in one place

   • Tender documents

   • Q&A and clarifications

   • Your final answers

   • Scores and feedback from the buyer

2. Tag submissions properly

   • Sector, region, value range

   • Outcome (win/loss)

   • Key reasons for result (price, quality, compliance)

3. Let your AI agent learn

   Skim, for example, trains your “Agent” on past successful bids and uses a feedback loop to improve its recommendations and draft quality over time.

Next year, when you ask “how do we win more government contracts?”, you’ll have a clear, data-backed answer instead of opinions.

Example: A 20-person consultancy winning its first big contract

Imagine a 20-person digital consultancy based in the EU:

• No dedicated bid team

• Strong private sector portfolio

• Wants to win its first €500k+ government contract

Old way:

• Sign up to TED and national portals

• Miss half the relevant notices

• Panic-write a 120-page bid over two weeks

• Lose, with vague feedback like “another bidder scored higher on quality”

New way with AI:

1. Connect to Skim and define an ideal tender profile (digital projects, €200k–€1m, specific regions and CPV codes).

2. Start receiving curated alerts from 4,500+ portals with a win-likelihood score.

3. Use AI bid/no-bid to qualify quickly. Only high-fit opportunities move forward.

4. When a good tender appears, Skim’s TenderGPT summarises requirements, pulls relevant past answers, and drafts first-round responses.

5. Consultants spend their time sharpening the narrative and pricing — not copying text between documents.

Same team size. Many more winnable shots on goal.

FAQ: Real questions people ask about winning government contracts

Is it actually realistic for SMEs to win government contracts?

Yes. Governments in the UK and EU have explicit policies to increase SME participation, and publish guidance to help small organisations bid effectively.

You still need to be organised and credible, but you’re not competing on size alone.

What’s the hardest part about winning public tenders?

For most teams, it’s not “understanding procurement” — it’s capacity:

• Finding relevant tenders in time

• Reading all the documents

• Writing compliant, tailored answers

That’s exactly where AI tender platforms (Skim, TenderStria, etc.) are focused: discovery, qualification, and drafting.

Do I need a professional bid writer?

A good bid writer is an advantage, especially on complex, high-value contracts. But many SMEs start by:

• Assigning a bid owner internally

• Using external reviewers selectively

• Letting AI handle structure, consistency, and first drafts

Think of AI as your junior bid writer and a human as the editor-in-chief.

Is AI allowed in government bids?

Yes — as long as:

• Your content is accurate, compliant, and original

• You can stand behind everything you submit

Government guidance focuses on outcomes and compliance, not the tools used to write the text. Just don’t paste unedited AI hallucinations into your final answers.

How to put this into action this week

Here’s a simple 5-item checklist you can actually do:

1. List your last 5 tenders (won or lost) and write one line: “why we really won/lost”.

2. Create a basic bid library with 3 case studies, your core policies, and a company overview.

3. Set up an AI tender platform like Skim and feed it those documents plus your ideal tender profile.

4. Agree an internal bid/no-bid scorecard with sales, delivery, and finance.

5. For the next tender you see, use AI to do the first draft — and measure how many hours you saved.

If the time saved and hit rate don’t improve, adjust your filters and your library — not your ambition.